For any Business and Management professional hoping to achieve fluency in skills that are common and essential across the 8 ICT jobs under the Business and Management job family: AI literacy, AI technologies, agile thinking, agile methodologies, creative thinking, critical thinking, communication, data analytics, ethical and Responsible AI, problem solving, solutioning, stakeholder engagement, prompt engineering and project management.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Essential common foundational skills needs across ICT job roles under the Business and Management job family for AI preparedness.
Course | Skills Developed | |
---|---|---|
Agile Explorer | IBM | Agile thinking, Agile methodologies |
AI Canon | AI Canon | AI literacy |
AI Essentials Course | AI literacy | |
AI Ethics | IBM | Ethical and Responsible AI, AI ethics and governance |
AI for Everyone by Andrew Ng | Coursera | AI literacy |
AI Fundamentals | IBM | AI Fundamentals |
Building AI Literacy | AI literacy | |
Building Career Agility and Resilience in the Age of AI | AI technologies skills to develop a "future-proof career mindset" | |
Develop Your Prompt Engineering Skills | Prompt engineering | |
Engaging Stakeholders for Success | Cisco | Communication, Stakeholder engagement, Change Management |
Explore Emerging Tech | IBM | Artificial intelligence, data, blockchain, cloud, cybersecurity, iot |
Foundations of Project Management | Google / Coursera | Project management |
Introduction to Artificial Intelligence | DIGITALEUROPE | Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Data Science Fundamentals, AI Ethics and Governance |
Introduction to Data Analytics | IBM / Coursera | Data analysis, data visualization, Microsoft Excel |
Introduction to modern AI | Cisco | AI literacy |
Introduction to Prompt Engineering | IBM / EDX | Prompt engineering |
Introduction to Responsible AI Skills | Cisco / Intel | Ethical and Responsible AI, AI ethics and governance |
Responsible AI Foundations | Ethical and Responsible AI, AI ethics and governance | |
Working in a Digital World: Professional Skills | IBM | Agile methodologies, business acumen, creative thinking, critical thinking, communication, problem solving, solutioning |
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For any Business analyst professional hoping to achieve fluency on principal skills like data analyst, Python programming, dashboard and data visualization.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Advanced Data Analytics Professional Certificate | Google / Coursera | Data Science, Data Analysis, Python Programming, Jupyter Notebook, Machine Learning, Statistical Analysis, Tableau Software, Data Visualization, Predictive Modelling, Kaggle |
Business Intelligence Certificate | Google / Coursera | Business Intelligence, Extraction, Transformation And Loading (ETL), Bigquery, Dashboarding and Reporting, Data Analysis, Data Modeling, Business Analysis, SQL, Tableau Software, Business Process |
Data Analysis with Python | IBM / Coursera | Model Selection, Data Analyst, Python Programming, Data Visualization, Predictive Modelling |
Data Analyst Capstone Project | IBM / Coursera | Data Analyst, Python Programming, Dashboard, Data visualization, SQL and RDBMS |
Data Analyst Professional Certificate | IBM / Coursera | Data science, Spreadsheet, Data Analysis, Python Programming, Microsoft Excel, Ibm Cognos Analytics, Dashboard, SQL, Numpy, Pandas, Data Visualization, Pivot Table |
Data Analytics Certificate | IBM | Data Classification; Data Usability for Organizations; Inferential and Descriptive Statistics; Data Collection and Analysis; Data Preparation for Analysis; and Data Visualization and Presentation |
Data Analytics Essentials | Cisco | Data analysis, Analytical skills |
Data Analytics Certificate | Google / Coursera | Data Analysis, Creating case studies, Data Visualization, Data Cleansing, Developing a portfolio, Data Collection, Spreadsheet, Metadata, SQL, Data Ethics, Data Aggregation, R Markdown |
Data Visualization and Dashboards with Excel and Cognos | IBM / Coursera | Data Analyst, Dashboard, Data visualization |
Databases and SQL for Data Science with Python | IBM / Coursera | Python Programming, SQL, Cloud databases |
Excel Basics for Data Analysis | IBM / Coursera | Data analysis, Pivot table |
Python for Data Science, AI & Development | IBM / Coursera | Python Programming, Panda, Numpy |
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For any Business Intelligence analyst professional hoping to achieve fluency on principal skills like data analyst, Python programming, dashboard, data visualization, Machine Learning and SAP and Microsoft analytic tools.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Advanced Data Analytics Professional Certificate | Google / Coursera | Data Science, Data Analysis, Python Programming, Jupyter Notebook, Machine Learning, Statistical Analysis, Tableau Software, Data Visualization, Predictive Modelling, Kaggle |
Business Intelligence Certificate | Google / Coursera | Business Intelligence, Extraction, Transformation And Loading (ETL), Bigquery, Dashboarding and Reporting, Data Analysis, Data Modeling, Business Analysis, SQL, Tableau Software, Business Process |
Data Analysis with Python | IBM / Coursera | Model Selection, Data Analyst, Python Programming, Data Visualization, Predictive Modelling |
Data Analyst Capstone Project | IBM / Coursera | Data Analyst, Python Programming, Dashboard, Data visualization, SQL and RDBMS |
Data Analyst Certificate | Google / Coursera | Data analysis, data visualization, Data driven decision making, Data-driven insights Responsible AI |
Data Analyst Professional Certificate | IBM / Coursera | Data science, Spreadsheet, Data Analysis, Python Programming, Microsoft Excel, IBM Cognos Analytics, Dashboard, SQL, Numpy, Pandas, Data Visualization, Pivot Table |
Data Visualization and Dashboards with Excel and Cognos | IBM / Coursera | Data Analyst, Dashboard, Data visualization |
Databases and SQL for Data Science with Python | IBM / Coursera | Python Programming, SQL, Cloud databases |
Excel Basics for Data Analysis | IBM / Coursera | Data analysis, Pivot table |
Getting Started with R for Data Science FEE |
Data analysis, R Programming | |
Machine Learning Specialization | Stanford / DeepLearning.AI | Logistic regression, Artificial Neural Network, Linear Regression, Decision Trees |
Machine Learning with Python Foundations | In this course, Frederick Nwanganga introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via the most in-demand language in use today, Python. Frederick starts with exactly what it means for machines to learn and the different ways they learn, then gets into how to collect, understand, and prepare data for machine learning. He also provides guided examples of how to accomplish each step using Python. Finally, he brings it all together to build, evaluate, and interpret the results of a machine learning model in Python. | |
Power BI: Integrating AI and Machine Learning FEE |
This course showcases existing AI and machine learning capabilities available directly in accessible Power BI functionalities. Data analytics and business analysis expert Helen Wall gives you a useful overview of Power BI, then dives into the steps to configure Power Query and your data model. Helen steps through analyzing single variables and shows you the tools and techniques to measure relationships between variables. She shows you visuals that you can use to pose and answer questions in Power BI, explains useful techniques to enhance your analysis of time series data, and walks you through some best practices for sharing your analysis. | |
Python for Data Science, AI & Development | IBM / Coursera | Python Programming, Panda, Numpy |
SAP analytics FEE |
SAP | Crystal Reports SAP BI Platform Administration SAP Lumira |
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For any Business systems analyst professional hoping to achieve fluency on principal skills like data analyst, Python programming, dashboard, data visualization, management and business processes.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Data Analysis with Python | IBM / Coursera | Model Selection, Data Analyst, Python Programming, Data Visualization, Predictive Modelling |
Data Analyst Capstone Project | IBM / Coursera | Data Analyst, Python Programming, Dashboard, Data visualization, SQL and RDBMS |
Data Analyst Certificate | Google / Coursera | Data analysis, data visualization, Data driven decision making, Data-driven insights Responsible AI |
Data Analyst Professional Certificate | IBM / Coursera | Data science, Spreadsheet, Data Analysis, Python Programming, Microsoft Excel, IBM Cognos Analytics, Dashboard, SQL, Numpy, Pandas, Data Visualization, Pivot Table |
Data Visualization and Dashboards with Excel and Cognos | IBM / Coursera | Data Analyst, Dashboard, Data visualization |
Databases and SQL for Data Science with Python | IBM / Coursera | Python Programming, SQL, Cloud databases |
Excel Basics for Data Analysis | IBM / Coursera | Data analysis, Pivot table |
Information Systems Specialization | Coursera / University of Minnesota | Analysis for Business Systems, Enterprise Systems, IT Infrastructure, IS/IT Governance |
Machine Learning Specialization | Stanford / DeepLearning.AI | Logistic regression, Artificial Neural Network, Linear Regression, Decision Trees |
Machine Learning with Python Foundations | In this course, Frederick Nwanganga introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via the most in-demand language in use today, Python. Frederick starts with exactly what it means for machines to learn and the different ways they learn, then gets into how to collect, understand, and prepare data for machine learning. He also provides guided examples of how to accomplish each step using Python. Finally, he brings it all together to build, evaluate, and interpret the results of a machine learning model in Python. | |
Python for Data Science, AI & Development | IBM / Coursera | Python Programming, Panda, Numpy |
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For any Customer Service Representative professional hoping to achieve fluency on principal skills like customer experience, data analysis, integrating AI solutions, laws and regulations on data protection and privacy and security.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Advance Your Data Privacy Skills | Data Privacy | |
AI in Customer Service FEE |
Udemy | Customer Service, integrating AI solutions |
Customer Service | IBM | Customer engagement, problem solving and process controls |
Data Analyst Capstone Project | IBM / Coursera | Data Analyst, Python Programming, Dashboard, Data visualization, SQL and RDBMS |
Data Analyst Certificate | Google / Coursera | Data analysis, data visualization, Data driven decision making, Data-driven insights Responsible AI |
Introduction to Cybersecurity | Cisco | Cybersecurity |
Machine Learning Specialization | Stanford / DeepLearning.AI | Logistic regression, Artificial Neural Network, Linear Regression, Decision Trees |
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For any Digital Marketing Specialist professional hoping to achieve fluency on principal skills like customer service, digital marketing, marketing, problem solving and process controls and social media.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Customer Service | IBM | Customer engagement, problem solving and process controls |
Digital Marketing and Ecommerce Certificate |
Google / Coursera | SEO, e-commerce, email marketing, Marketing |
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For any Product Manager professional hoping to achieve fluency on principal skills like artificial intelligence, data analysis, product Design, UX design and Product management.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI Product Manager Professional Certificate | IBM / Coursera | Artificial intelligence, Product management, AI product manager, Prompt engineering |
Data Analyst Certificate | Google / Coursera | Data analysis, data visualization, Data driven decision making, Data-driven insights Responsible AI |
Data Analyst Professional Certificate | IBM / Coursera |
Data Analyst, Python Programming, Dashboard, Data visualization, SQL and RDBMS |
User Experience Design | IBM | Design user-centered digital products, Product Design, User Experience |
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For any Project Manager professional hoping to achieve fluency on principal skills like artificial intelligence, agile Management, change management, data analysis, project management, project planning and developing, problem Solving, prompt engineering and risk management.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Artificial Intelligence Online Community (Resource) | Project Management Institute | Artificial intelligence |
Project Management Certificate |
Google / Coursera | Agile Management, Change Management, Data analysis, Project management, Project planning and developing, Problem Solving and Project risk management, Strategic thinking |
Project Manager | IBM | Project management, Project planning and developing, Problem Solving and Project risk management |
Project Manager Professional Certificate | IBM / Coursera | Developing project timelines, roles and responsibility matrices, stakeholder management tools, and communications plans |
Talking to AI: Prompt Engineering for Project Managers FEE |
Project Management Institute | Artificial intelligence, Prompt engineering |
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For any Senior Product Manager professional hoping to achieve fluency on principal skills like artificial intelligence, data analysis, Jira, product design, user experience, and product management.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI Product Manager Professional Certificate | IBM / Coursera | Artificial intelligence, Product management, AI product manager, Prompt engineering |
Data Analyst Certificate | Google / Coursera | Data analysis, data visualization, Data driven decision making, Data-driven insights Responsible AI |
Data Analyst Professional Certificate | IBM / Coursera | Data Analyst, Python Programming, Dashboard, Data visualization, SQL and RDBMS |
Learning Jira | Jira | |
User Experience Design | IBM | Design user-centered digital products, Product Design, User Experience |
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For any Cybersecurity professional hoping to achieve fluency in skills that are common and essential across the 4 ICT jobs under the Cybersecurity job family: AI literacy, AI Security, AI technologies, agile thinking, agile methodologies, creative thinking, critical thinking, communication, cybersecurity, data analytics, ethical and Responsible AI, problem solving, solutioning, stakeholder engagement, and prompt engineering.
Essential common foundational skills needs across ICT job roles under the Cybersecurity job family for AI preparedness.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Agile Explorer | IBM | Agile thinking, Agile methodologies |
AI Canon | AI Canon | AI literacy |
AI Essentials Course | AI literacy | |
AI Ethics | IBM | Ethical and Responsible AI, AI ethics and governance |
AI for Everyone by Andrew Ng | Coursera | AI literacy |
AI Fundamentals | IBM | AI Fundamentals |
AI Security Nuggets | Cisco | AI regulations, AI threat modeling, AI supply chain, Retrieval Augmented Generation (RAG), LLM stack |
Building AI Literacy | AI literacy | |
Building Career Agility and Resilience in the Age of AI | AI technologies skills to develop a "future-proof career mindset" | |
Creating compelling Reports | Cisco | Communication, presentation |
Cybersecurity Essentials | Cisco | Cybersecurity literacy, Asset protection, Security response, Network protection, Product expertise, Data breach analysis, Data defense, Cybersecurity policies |
Cybersecurity Fundamentals | IBM | Cybersecurity literacy, Cryptography, Cyber Attacks, Cyber threat analysis, Cyber threat analysis intelligence, Cybersecurity risk management |
Develop Your Prompt Engineering Skills | Prompt engineering | |
Engaging Stakeholders for Success | Cisco | Communication, Stakeholder engagement, Change Management |
Explore Emerging Tech | IBM | Artificial intelligence, data, blockchain, cloud, cybersecurity, iot |
Introduction to Artificial Intelligence | DIGITALEUROPE | Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Data Science Fundamentals, AI Ethics and Governance |
Introduction to Data Analytics | IBM / Coursera | Data analysis, data visualization, Microsoft excel |
Introduction to modern AI | Cisco | AI literacy |
Introduction to Prompt Engineering | IBM / EDX | Prompt engineering |
Introduction to Responsible AI Skills | Cisco / Intel | Ethical and Responsible AI, AI ethics and governance |
Responsible AI Foundations | Ethical and Responsible AI, AI ethics and governance | |
Working in a Digital World: Professional Skills | IBM | Agile methodologies, business acumen, creative thinking, critical thinking, communication, problem solving, solutioning |
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For any Cybersecurity Analyst professional hoping to achieve fluency on principal skills like vulnerability management, risk analysis, security policies, risk management, firewall, security information and event management (SIEM), information systems security, governance, vulnerability assessments, penetration testing, access controls, malware analysis.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Cybersecurity Analyst Professional Certificate | IBM / Coursera | Information security analyst, Junior cybersecurity analyst, IT security analyst, security analyst |
Cybersecurity Certificate | IBM | Governance, Risk, Compliance and Data Privacy; Vulnerability Management; System and Network Security; Cloud Security; Security Operations Management; Incident Response and System Forensics |
Cybersecurity Certificate | Google / Coursera | Python Programming, SQL, Linux, IDS, Security Information and Event Management (SIEM) tools |
Junior Cybersecurity Analyst Career path | Cisco | Vulnerability management, risk analysis, security policies, risk management, firewall, security information and event management (SIEM), information systems security, governance, vulnerability assessments, penetration testing, access controls, malware analysis |
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For any Ethical Hacker professional hoping to achieve fluency on principal skills like ethical hacking, penetration testing, vulnerability scanning, social engineering, exploiting networks, exploiting applications, IoT security, vulnerability assessment, reporting and pen testing tools.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Ethical Hacker |
Cisco | Ethical Hacking, Penetration Testing, Vulnerability Scanning, Social, Engineering, Exploiting Networks, Exploiting Applications, IoT Security, Vulnerability Assessment, Reporting, Pen testing Tools |
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For any Information Security Specialist professional hoping to achieve fluency on principal skills like Cyber threat intelligence, Information assurance, Encryption, Firewall Incident response, Security policies, risk analysis, security policies and Vulnerability management.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Cyber Threat Intelligence | IBM / Coursera | Cybersecurity, network defensive tactics, threat intelligence, Application Security, security analyst |
Cybersecurity Analyst Professional Certificate | IBM / Coursera | Information security analyst, Junior cybersecurity analyst, IT security analyst, security analyst |
Cybersecurity Capstone: Breach Response Case Studies | IBM / Coursera | Computer Security Incident Management, Cybersecurity, Breach (Security Exploit), security analyst, cyber attack |
Cybersecurity Certificate | IBM | Governance, Risk, Compliance, and Data Privacy; Vulnerability Management; System and Network Security; Cloud Security; Security Operations Management; and Incident Response and System Forensics |
Cybersecurity Compliance Framework, Standards & Regulations | IBM / Coursera | Risk Management, Laws and Regulations, Cybersecurity Compliance, Cybersecurity Framework, Cybersecurity Standards |
Cybersecurity Certificate | Google / Coursera | Python Programming, SQL, Linux, IDS, Security Information and Event Management (SIEM) tools |
Junior Cybersecurity Analyst Career path | Cisco | Vulnerability management, risk analysis, security policies, risk management, firewall, security information and event management (SIEM), information systems security, governance, vulnerability assessments, penetration testing, access controls, malware analysis |
Network Security & Database Vulnerabilities | IBM / Coursera | Networking basics, Cybersecurity, Network Security, database vulnerabilities, Sql Injection |
Operating Systems: Overview, Administration, and Security | IBM / Coursera | Operating Systems, Directory and File Management, User (Computing), Virtualization, Linux, Windows, MacOS, User Accounts |
Penetration Testing, Incident Response and Forensics | IBM / Coursera | Computer Security Incident Management, scripting, Cybersecurity, forensics, Penetration Test |
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For any Soc Analyst Level 1 professional hoping to achieve fluency on principal skills like attack methods, computer forensics, cryptography, cybersecurity, data and event analysis, endpoint threat analysis, host-based analysis, incident response, malware analysis, network attacks, network intrusion analysis secOps, security concepts, security monitoring, security policy, security procedures, SOC metrics and threat detection.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Cisco - CyberOps Associate (*) | Cisco | Attack methods, computer forensics, cryptography, cybersecurity, data and event analysis, endpoint threat analysis, host-based analysis, incident response, malware analysis, network attacks, network intrusion analysis secops, security concepts, security monitoring, security policy, security procedures, SOC metrics, threat detection |
Machine Learning Specialization | Stanford / DeepLearning.AI | Logistic regression, Artificial Neural Network, Linear Regression, Decision Trees |
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(*) Instructor-led courses are free for Academic Institutions. These Institutions may charge fees for Instructor-led classes.
For any Data Science professional hoping to achieve fluency in skills that are common and essential across the 4 ICT jobs under the Data Science job family: AI literacy, AI technologies, agile thinking, agile methodologies, creative thinking, critical thinking, communication, data analytics, ethical and responsible AI, problem solving, solutioning, stakeholder engagement, prompt engineering and project management.
Essential common foundational skills needs across ICT job roles under the Data Science family for AI preparedness
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Agile Explorer | IBM | Agile thinking, Agile methodologies |
AI Canon | AI Canon | AI literacy |
AI Essentials Course | AI literacy | |
AI Ethics | IBM | Ethical and Responsible AI, AI ethics and governance |
AI for Everyone by Andrew Ng | Coursera | AI literacy |
AI Fundamentals | IBM | AI Fundamentals |
Building AI Literacy | AI literacy | |
Building Career Agility and Resilience in the Age of AI | AI technologies skills to develop a "future-proof career mindset" | |
Creating compelling Reports | Cisco | Communication, presentation |
Data Analytics Certificate | IBM | Data Classification; Data Usability for Organizations; Inferential and Descriptive Statistics; Data Collection and Analysis; Data Preparation for Analysis; and Data Visualization and Presentation |
Develop Your Prompt Engineering Skills | Prompt engineering | |
Engaging Stakeholders for Success | Cisco | Communication, Stakeholder engagement, Change Management |
Explore Emerging Tech | IBM | Artificial intelligence, data, blockchain, cloud, cybersecurity, iot |
Introduction to Artificial Intelligence | DIGITALEUROPE | Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Data Science Fundamentals, AI Ethics and Governance |
Introduction to Data Analytics | IBM / Coursera | Data analysis, data visualization, Microsoft Excel |
Introduction to modern AI | Cisco | AI literacy |
Introduction to Prompt Engineering | IBM / EDX | Prompt engineering |
Introduction to Responsible AI Skills | Cisco / Intel | Ethical and Responsible AI, AI ethics and governance |
Responsible AI Foundations | Ethical and Responsible AI, AI ethics and governance | |
Working in a Digital World: Professional Skills | IBM | Agile methodologies, business acumen, creative thinking, critical thinking, communication, problem solving, solutioning |
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For any Data Analyst professional hoping to achieve fluency on principal skills like SQL, Python, Microsoft Excel, data visualization, data management, R, data governance, data management and data modeling.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Advanced Data Analytics Professional Certificate | Google / Coursera | Data Science, Data Analysis, Python Programming, Jupyter Notebook, Machine Learning, Statistical Analysis, Tableau Software, Data Visualization, Predictive Modelling, Kaggle |
Data Analysis with Python | IBM / Coursera | Model Selection, Data Analyst, Python Programming, Data Visualization, Predictive Modelling |
Data Analyst Capstone Project | IBM / Coursera | Data Analyst, Python Programming, Dashboard, Data visualization, SQL and RDBMS |
Data Analyst Professional Certificate | IBM / Coursera | Data science, Spreadsheet, Data Analysis, Python Programming, Microsoft Excel, IBM Cognos Analytics, Dashboard, SQL, Numpy, Pandas, Data Visualization, Pivot Table |
Data Analytics Certificate | IBM | Data Classification; Data Usability for Organizations; Inferential and Descriptive Statistics; Data Collection and Analysis; Data Preparation for Analysis; and Data Visualization and Presentation |
Data Analytics Essentials | Cisco | Data analysis, Analytical skills |
Data Analytics Certificate | Google / Coursera | Data Analysis, Creating case studies, Data Visualization, Data Cleansing, Developing a portfolio, Data Collection, Spreadsheet, Metadata, SQL, Data Ethics, Data Aggregation, Data Aggregation, R Markdown |
Data Visualization and Dashboards with Excel and Cognos | IBM / Coursera | Data Analyst, Dashboard, Data visualization |
Databases and SQL for Data Science with Python | IBM / Coursera | Python Programming, SQL, Cloud databases |
Excel Basics for Data Analysis | IBM / Coursera | Data analysis, Pivot table |
Python for Data Science, AI & Development | IBM / Coursera | Python Programming, Panda, Numpy |
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For any Data Engineer professional hoping to achieve fluency on principal skills like Python programming, Apache NiFi, Apache Airflow and Tableau.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Data Engineering Pipeline Management with Apache Airflow FEE |
In this course, certified Google cloud architect and data engineer Janani Ravi guides you through using Apache Airflow to complete your data engineering pipeline management workflows. Learn how to work with role-based access control, including creating users with different roles, executing a branching DAG and a SQL DAG, recalling actions that users with different roles can perform, and more. Go over how to manage SLAs and schedule DAGs with datasets. Find out how to work with AirFlow plugins and explore the CSV reader plugin. Plus, discover how to scale Apache Airflow, set up a data transformation pipeline, execute tasks, and more. | |
Data Management with Apache NiFi FEE |
If you are a data management professional, this course can give you the understanding you need to get started with this powerful tool. Janani Ravi guides you through getting started with Apache NiFi. Learn about core concepts and architecture, as well as how to download, start, and log into Apache NiFi on both macOS and Windows. Find out how to build and run data flows and how to integrate NiFi with PostgreSQL. Explore ways to configure and use NiFi processors and processing groups and integrate NiFi with Amazon S3. Plus, discover advanced features of NiFi dataflows like configuring back pressure, using a funnel in the dataflow, setting up monitoring and configuring alerts for a dataflow, and much more. | |
Machine Learning with Python Foundations | In this course, Frederick Nwanganga introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via the most in-demand language in use today, Python. Frederick starts with exactly what it means for machines to learn and the different ways they learn, then gets into how to collect, understand, and prepare data for machine learning. He also provides guided examples of how to accomplish each step using Python. Finally, he brings it all together to build, evaluate, and interpret the results of a machine learning model in Python. | |
SQL Server Machine Learning Services with Python | Learn how to analyze SQL Server data with Python. Database expert Adam Wilbert shows how to use a powerful combination of tools, including high-performance Python libraries and the Machine Learning Services add-on, directly inside SQL Server to streamline analysis. Adam shows how to use Python scripts to perform statistical analysis, generate graphics such as scatterplots and bar charts, and process tabular data. He also explains how to turn a Python script into a stored procedure and set up standalone ML services to execute scripts without impacting SQL Server performance. | |
Training Neural Networks in Python | This course by Eduardo Corpeño teaches the inner workings of neural networks in Python, allowing you to fully understand the algorithms behind them. Although there are professional tools that allow you to train neural networks from a high-level perspective, this course gives you a chance to tap into the details of the algorithms behind neural networks. Through exercises and examples, learn how to relate biological neurons to Python elements to build and train your own networks, and gain knowledge that can help you choose the right neural network architecture and training method for your projects and problems you encounter. |
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For any Data Scientist professional hoping to achieve fluency on principal skills like Big Data Technologies, Tools, and Techniques, Data Mining, Data Mining, Data Modeling, Statistical Analysis Programming Languages and Machine Learning Frameworks.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
IBM Data Science Certificate | IBM / Coursera | Big Data Technologies, Tools, and Techniques, Data Mining, Data Mining, Data Modeling, Statistical Analysis Programming Languages, Machine Learning Frameworks |
Machine Learning Specialization | Stanford / DeepLearning.AI | Logistic regression, Artificial Neural Network, Linear Regression, Decision Trees |
Machine Learning with Python Foundations | In this course, Frederick Nwanganga introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via the most in-demand language in use today, Python. Frederick starts with exactly what it means for machines to learn and the different ways they learn, then gets into how to collect, understand, and prepare data for machine learning. He also provides guided examples of how to accomplish each step using Python. Finally, he brings it all together to build, evaluate, and interpret the results of a machine learning model in Python. | |
MIT Statistics and Data Science Certificate FEE |
EDX | Big Data Technologies, Tools, and Techniques, Data Mining, Data Mining, Data Modeling, Statistical Analysis Programming Languages, Machine Learning Framework |
Python for Data Science, AI & Development | IBM / Coursera | Python Programming, Panda, Numpy |
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For any Data Specialist professional hoping to achieve fluency on principal skills like Python programming, Apache NiFi, Apache Airflow and Tableau.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Data Management with Apache NiFi FEE |
If you are a data management professional, this course can give you the understanding you need to get started with this powerful tool. Janani Ravi guides you through getting started with Apache NiFi. Learn about core concepts and architecture, as well as how to download, start, and log into Apache NiFi on both macOS and Windows. Find out how to build and run data flows and how to integrate NiFi with PostgreSQL. Explore ways to configure and use NiFi processors and processing groups and integrate NiFi with Amazon S3. Plus, discover advanced features of NiFi dataflows like configuring back pressure, using a funnel in the dataflow, setting up monitoring and configuring alerts for a dataflow, and much more. | |
Machine Learning with Python Foundations | In this course, Frederick Nwanganga introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via the most in-demand language in use today, Python. Frederick starts with exactly what it means for machines to learn and the different ways they learn, then gets into how to collect, understand, and prepare data for machine learning. He also provides guided examples of how to accomplish each step using Python. Finally, he brings it all together to build, evaluate, and interpret the results of a machine learning model in Python. | |
Power BI: Integrating AI and Machine Learning FEE |
This course showcases existing AI and machine learning capabilities available directly in accessible Power BI functionalities. Data analytics and business analysis expert Helen Wall gives you a useful overview of Power BI, then dives into the steps to configure Power Query and your data model. Helen steps through analyzing single variables and shows you the tools and techniques to measure relationships between variables. She shows you visuals that you can use to pose and answer questions in Power BI, explains useful techniques to enhance your analysis of time series data, and walks you through some best practices for sharing your analysis. | |
SQL Server Machine Learning Services with Python | Learn how to analyze SQL Server data with Python. Database expert Adam Wilbert shows how to use a powerful combination of tools, including high-performance Python libraries and the Machine Learning Services add-on, directly inside SQL Server to streamline analysis. Adam shows how to use Python scripts to perform statistical analysis, generate graphics such as scatterplots and bar charts, and process tabular data. He also explains how to turn a Python script into a stored procedure and set up standalone ML services to execute scripts without impacting SQL Server performance. | |
Training Neural Networks in Python | This course by Eduardo Corpeño teaches the inner workings of neural networks in Python, allowing you to fully understand the algorithms behind them. Although there are professional tools that allow you to train neural networks from a high-level perspective, this course gives you a chance to tap into the details of the algorithms behind neural networks. Through exercises and examples, learn how to relate biological neurons to Python elements to build and train your own networks, and gain knowledge that can help you choose the right neural network architecture and training method for your projects and problems you encounter. |
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For any Design and User Experience professional hoping to achieve fluency in skills that are common and essential across the 3 ICT jobs under the Design and User Experience job family: AI literacy, AI technologies, agile thinking, agile methodologies, creative thinking, critical thinking, communication, data analytics, Design Thinking, ethical and responsible AI, innovation, problem solving, solutioning, stakeholder engagement and prompt engineering.
Essential common foundational skills needs across ICT job roles under the Data Science family for AI preparedness
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Agile Explorer | IBM | Agile thinking, Agile methodologies |
AI Canon | AI Canon | AI literacy |
AI Essentials Course | AI literacy | |
AI Ethics | IBM | Ethical and Responsible AI, AI ethics and governance |
AI for Everyone by Andrew Ng | Coursera | AI literacy |
AI Fundamentals | IBM | AI Fundamentals |
Building AI Literacy | AI literacy | |
Building Career Agility and Resilience in the Age of AI | AI technologies skills to develop a "future-proof career mindset" | |
Develop Your Prompt Engineering Skills | Prompt engineering | |
Engaging Stakeholders for Success | Cisco | Communication, Stakeholder engagement, Change Management |
Enterprise Design Thinking Co-Creator | IBM | Design Thinking, creativity, innovation |
Enterprise Design Thinking Practitioner | IBM | Design Thinking, creativity, innovation |
Explore Emerging Tech | IBM | Artificial intelligence, data, blockchain, cloud, cybersecurity, iot |
Introduction to Artificial Intelligence | DIGITALEUROPE | Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Data Science Fundamentals, AI Ethics and Governance |
Introduction to Data Analytics | IBM / Coursera | Data analysis, data visualization, Microsoft Excel |
Introduction to modern AI | Cisco | AI literacy |
Introduction to Prompt Engineering | IBM / EDX | Prompt engineering |
Introduction to Responsible AI Skills | Cisco / Intel | Ethical and Responsible AI, AI ethics and governance |
Responsible AI Foundations | Ethical and Responsible AI, AI ethics and governance | |
Working in a Digital World: Professional Skills | IBM | Agile methodologies, business acumen, creative thinking, critical thinking, communication, problem solving, solutioning |
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For any Design Engineer professional hoping to achieve fluency on principal skills like AI powered programming, Machine Learning tools, Azure AI and Generative design foundations.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI and Machine Learning Tools for After Effects FEE |
Adobe After Effects users can tap into a variety of features and third-party add-ons to streamline tedious tasks, generate imagery, colorize footage, fix lighting problems, and much more. In this course, Eran Stern explores the ways AI and machine learning are transforming motion graphics for the better—to, in his words, "stay creative in an AI world." | |
AI Powered Programming with GitHub CoPilot FEE |
In this course, technical trainer and content developer Tim Warner provides comprehensive coverage of GitHub Copilot's capabilities. After a chance to brush up on basics, build your understanding of Copilot and how you can integrate it with your IDE. Learn how to apply GitHub Copilot in coding and enhance your coding with comment-based generation. Find out how to leverage Copilot in your unit testing. Plus, discover how to use GitHub Copilot to build and deploy an app. | |
Applying Generative AI as a Creative Professional | From images to video to audio, generative AI is transforming creative endeavors of all kinds. Learn how generative AI technologies can accelerate the brainstorm process, streamline tedious tasks, and expand your creative options. Discover the benefits of generative AI. Learn how AI tools can increase creative output. Explore the ethical considerations behind AI. | |
Azure AI Engineering: Speech, Language, and Vision Solutions FEE |
This course introduces fundamental concepts related to artificial intelligence (AI) as well as the services in Microsoft Azure that can be used to build AI solutions. With expert instruction from Microsoft Learn, develop the skills required to use Azure services to create speech-enabled apps, translate speech, build a conversational language understanding model, develop apps with Azure AI Language, build a question-answering solution, and more. By the end of this course, you’ll also be prepared to create a custom text classification solution, train and evaluate models, analyze images and video, and detect, analyze, and recognize images and faces. | |
Generative Design Foundations FEE |
This course introduces this emerging technology for architecture, engineering, urban planning, and industrial design. Designer Danil Nagy explains the four key pillars of generative design: creating a parametric design space, evaluating performance using computer simulation, automatically generating design solutions through optimization, and evaluating the results to discover the best design options. He then introduces the tools and software you need to start integrating generative design into your workflows today. |
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For any Design Engineer professional hoping to achieve fluency on principal skills like AI powered programming, Machine Learning tools, Azure AI and Generative design foundations.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI and Machine Learning Tools for After Effects FEE |
Adobe After Effects users can tap into a variety of features and third-party add-ons to streamline tedious tasks, generate imagery, colorize footage, fix lighting problems, and much more. In this course, Eran Stern explores the ways AI and machine learning are transforming motion graphics for the better—to, in his words, "stay creative in an AI world." | |
AI Powered Programming with GitHub CoPilot FEE |
In this course, technical trainer and content developer Tim Warner provides comprehensive coverage of GitHub Copilot's capabilities. After a chance to brush up on basics, build your understanding of Copilot and how you can integrate it with your IDE. Learn how to apply GitHub Copilot in coding and enhance your coding with comment-based generation. Find out how to leverage Copilot in your unit testing. Plus, discover how to use GitHub Copilot to build and deploy an app. | |
Applying Generative AI as a Creative Professional | From images to video to audio, generative AI is transforming creative endeavors of all kinds. Learn how generative AI technologies can accelerate the brainstorm process, streamline tedious tasks, and expand your creative options. Discover the benefits of generative AI. Learn how AI tools can increase creative output. Explore the ethical considerations behind AI. | |
Azure AI Engineering: Speech, Language, and Vision Solutions FEE |
This course introduces fundamental concepts related to artificial intelligence (AI) as well as the services in Microsoft Azure that can be used to build AI solutions. With expert instruction from Microsoft Learn, develop the skills required to use Azure services to create speech-enabled apps, translate speech, build a conversational language understanding model, develop apps with Azure AI Language, build a question-answering solution, and more. By the end of this course, you’ll also be prepared to create a custom text classification solution, train and evaluate models, analyze images and video, and detect, analyze, and recognize images and faces. | |
Generative Design Foundations FEE |
This course introduces this emerging technology for architecture, engineering, urban planning, and industrial design. Designer Danil Nagy explains the four key pillars of generative design: creating a parametric design space, evaluating performance using computer simulation, automatically generating design solutions through optimization, and evaluating the results to discover the best design options. He then introduces the tools and software you need to start integrating generative design into your workflows today. |
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For any UX Designer professional hoping to achieve fluency on principal skills like AI powered programming, Machine Learning Tools, Azure AI, generative design foundations and UX design foundations.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
User Experience Design | IBM | UX Design |
UX Design Certificate | Google / Coursera | User Experience (UX), Prototype, Wireframe, User Experience Design (UXD), UX Research, mockup, Figma, Usability Testing, UX design jobs |
Applying Generative AI as a Creative Professional | From images to video to audio, generative AI is transforming creative endeavors of all kinds. Learn how generative AI technologies can accelerate the brainstorm process, streamline tedious tasks, and expand your creative options. Discover the benefits of generative AI. Learn how AI tools can increase creative output. Explore the ethical considerations behind AI. | |
AI and Machine Learning Tools for After Effects FEE |
Adobe After Effects users can tap into a variety of features and third-party add-ons to streamline tedious tasks, generate imagery, colorize footage, fix lighting problems, and much more. In this course, Eran Stern explores the ways AI and machine learning are transforming motion graphics for the better—to, in his words, "stay creative in an AI world." | |
Generative Design Foundations FEE |
This course introduces this emerging technology for architecture, engineering, urban planning, and industrial design. Designer Danil Nagy explains the four key pillars of generative design: creating a parametric design space, evaluating performance using computer simulation, automatically generating design solutions through optimization, and evaluating the results to discover the best design options. He then introduces the tools and software you need to start integrating generative design into your workflows today. |
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For any Infrastructure and Operations professional hoping to achieve fluency in skills that are common and essential across the 10 ICT jobs under the Infrastructure and Operations job family: AI literacy, AI technologies, agile thinking, agile methodologies, creative thinking, critical thinking, communication, data analytics, ethical and responsible AI, problem solving, retrieval augmented generation (RAG), solutioning, stakeholder engagement, prompt engineering and project management.
Essential common foundational skills needs across ICT job roles under the Data Science family for AI preparedness
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Agile Explorer | IBM | Agile thinking, Agile methodologies |
AI Canon | AI Canon | AI literacy |
AI Ecosystem overview | DIGITALEUROPE | AI ecosystem analysis, Understanding AI infrastructure, AI governance and regulation knowledge, Evaluating AI tools and platforms, Ethical AI decision-making |
AI Essentials Course | AI literacy | |
AI Ethics | IBM | Ethical and Responsible AI, AI ethics and governance |
AI for Everyone by Andrew Ng | Coursera | AI literacy |
AI Fundamentals | IBM | AI Fundamentals |
Building AI Literacy | AI literacy | |
Building Career Agility and Resilience in the Age of AI | AI technologies skills to develop a "future-proof career mindset" | |
Creating compelling Reports | Cisco | Communication, presentation |
Develop Your Prompt Engineering Skills | Prompt engineering | |
Engaging Stakeholders for Success | Cisco | Communication, Stakeholder engagement, Change Management |
Explore Emerging Tech | IBM | Artificial intelligence, data, blockchain, cloud, cybersecurity, iot |
Introduction to Artificial Intelligence | DIGITALEUROPE | Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Data Science Fundamentals, AI Ethics and Governance |
Introduction to Data Analytics | IBM / Coursera | Data analysis, data visualization, Microsoft Excel |
Introduction to modern AI | Cisco | AI literacy |
Introduction to Prompt Engineering | IBM / EDX | Prompt engineering |
Introduction to Responsible AI Skills | Cisco / Intel | Ethical and Responsible AI, AI ethics and governance |
Introduction to Retrieval Augmented Generation (RAG) | Cisco U | Retrieval-augmented Generation |
Introduction to Retrieval Augmented Generation (RAG) FEE |
Duke University / Coursera | Python programming, machine learning, retrieval augmented generation, large language models |
Responsible AI Foundations | Ethical and Responsible AI, AI ethics and governance | |
Working in a Digital World: Professional Skills | IBM | Agile methodologies, business acumen, creative thinking, critical thinking, communication, problem solving, solutioning |
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For any Database Administrator professional hoping to achieve fluency on principal skills like AI security, artificial neural networks and Microsoft SQL server.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI Security Nuggets | Cisco | AI regulations, AI threat modeling, AI supply chain, Retrieval Augmented Generation (RAG), LLM stack |
How to Master Database Troubleshooting | Database troubleshooting | |
Introduction to Networking and Cloud Computing | Microsoft / Coursera | Cloud computing, Network Monitoring, Network Security, Computer Network |
Machine Learning Specialization | Stanford / DeepLearning.AI | Logistic regression, Artificial Neural Network, Linear Regression, Decision Trees |
Securing the Use of Generative AI in Your Organization | This course with instructor Jerich Beason seeks to equip you with the knowledge and skills to navigate the evolving landscape of AI security, enabling you to confidently leverage generative AI while mitigating risks, safeguarding sensitive information, and fortifying their organization's digital resilience. Learn about the cybersecurity risks of generative AI, how to implement effective governance, risk, and compliance (GRC) processes for LLMs, the fundamentals for detecting and mitigating attacks on generative AI, and the ethical considerations of generative AI. Jerich ends the course with a look at some important AI security strategies and frameworks. | |
SQL Server Machine Learning Services with Python | Learn how to analyze SQL Server data with Python. Database expert Adam Wilbert shows how to use a powerful combination of tools, including high-performance Python libraries and the Machine Learning Services add-on, directly inside SQL Server to streamline analysis. Adam shows how to use Python scripts to perform statistical analysis, generate graphics such as scatterplots and bar charts, and process tabular data. He also explains how to turn a Python script into a stored procedure and set up standalone ML services to execute scripts without impacting SQL Server performance. | |
Training Neural Networks in Python | This course by Eduardo Corpeño teaches the inner workings of neural networks in Python, allowing you to fully understand the algorithms behind them. Although there are professional tools that allow you to train neural networks from a high-level perspective, this course gives you a chance to tap into the details of the algorithms behind neural networks. Through exercises and examples, learn how to relate biological neurons to Python elements to build and train your own networks, and gain knowledge that can help you choose the right neural network architecture and training method for your projects and problems you encounter. |
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For any Help Desk Analyst professional hoping to achieve fluency on principal skills like diagnose and troubleshoot, provide technical support, install and configure, educate and train, document and track, escalate complex problems, monitor system performance, prioritize and manage requests and provide excellent customer service.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Customer Service | IBM | Customer engagement, problem solving and process controls |
IT Essentials (*) | Cisco | Help Desk Support, Customer Service |
IT Help Desk for Beginner | Customer Service, Help Desk Support, troubleshooting, incident response | |
Network Technician Career path | Cisco | System Administration, Operating Systems (Linux, Windows 10), Local Area Networks (LANs), TCP/IP, Technical Support, Cybersecurity |
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(*) Instructor-led courses are free for Academic Institutions. These Institutions may charge fees for Instructor-led classes.
For any IT Manager professional hoping to achieve fluency on principal skills like cybersecurity risks of generative AI, how to implement effective governance, risk, and compliance (GRC) processes for LLMs, Google Cloud Machine Learning, AWS Machine Learning, GPT models, embedding models, codex models, and DALL-E models.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Azure OpenAI: Generative AI Models and How to Use Them | In this course, instructor Sammy Deprez introduces you to Azure OpenAI services and dives into the models that are available, including GPT models, embedding models, codex models, and DALL-E models. Sammy explains what each model type is and how it works, and he offers recommendations on the best way to use it. Plus, he discusses copyright issues and goes over how to combine models and start building your own solutions. | |
Data Engineering Pipeline Management with Apache Airflow FEE |
In this course, certified Google cloud architect and data engineer Janani Ravi guides you through using Apache Airflow to complete your data engineering pipeline management workflows. Learn how to work with role-based access control, including creating users with different roles, executing a branching DAG and a SQL DAG, recalling actions that users with different roles can perform, and more. Go over how to manage SLAs and schedule DAGs with datasets. Find out how to work with AirFlow plugins and explore the CSV reader plugin. Plus, discover how to scale Apache Airflow, set up a data transformation pipeline, execute tasks, and more. | |
Prepare for the AWS Certified Machine Learning Specialty (MLS-C01) | This learning path is for anyone looking to earn their AWS Certified Machine Learning - Specialty certification. Earning this certification validates expertise in building, training, tuning, and deploying machine learning models on AWS. To learn more about this certification, visit Amazon's website[MOU1] . Understand the skills and technologies to earn your MLS-C01 certification. Expand knowledge of machine learning. Learn concepts applicable to the certification. | |
Prepare for the Google Cloud Professional Machine Learning Engineer Certification | Those who have earned their Google Cloud Professional Machine Learning Engineer certification have shown their ability to design, build, and deploy machine learning models on the Google Cloud Platform. The courses in this learning path map to the skills and technologies for this certification exam. For more information, visit the Google website. Identify[MOU1] machine learning solutions for business problems. Demonstrate your ability to manage machine learning models. Study for the official Google certification exam. | |
Securing the Use of Generative AI in Your Organization | This course with instructor Jerich Beason seeks to equip you with the knowledge and skills to navigate the evolving landscape of AI security, enabling you to confidently leverage generative AI while mitigating risks, safeguarding sensitive information, and fortifying their organization's digital resilience. Learn about the cybersecurity risks of generative AI, how to implement effective governance, risk, and compliance (GRC) processes for LLMs, the fundamentals for detecting and mitigating attacks on generative AI, and the ethical considerations of generative AI. Jerich ends the course with a look at some important AI security strategies and frameworks. |
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For any IT Support Technician professional hoping to achieve fluency on principal skills like Automation, End-user training, Issue tracking, Microsoft Windows, Planning, Project management, Software installation, Testing methodologies, Virtual private networks and Windows servers.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Cloud Computing and Virtualization | IBM | Cloud computing; virtualization |
Customer Service | IBM | Customer engagement, problem solving and process controls |
Foundations of Project Management | Google / Coursera | Project management |
IT Essentials (*) | Cisco | Help Desk Support, Customer Service |
IT Help Desk for Beginner | Customer Service, Help Desk Support, troubleshooting, incident response | |
IT Security and Compliance | IBM | Security |
IT Support Certificate | IBM / Coursera | Computer assembly, wireless networking, installing programs, and customer service |
IT Support Technician Certificate | IBM | Computer assembly, wireless networking, installing programs, and customer service |
Network Technician Career path | Cisco | System Administration, Operating Systems (Linux, Windows 10), Local Area Networks (LANs), TCP/IP, Technical Support, Cybersecurity |
Software and Operating Systems | IBM | Manage and troubleshoot software and operating systems issues, configure settings, conclude the type of issue, follow troubleshooting steps and best practices, perform system updates, select tools for resolving issues across operating systems, perform user management tasks |
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(*) Instructor-led courses are free for Academic Institutions. These Institutions may charge fees for Instructor-led classes.
For any Network Administrator professional hoping to achieve fluency on principal skills like Ethernet, IP connectivity, IP services, IP subnetting, IPv4 And IPv6, addressing, network fundamentals, security fundamentals, switching, dynamic routing, Network Address Translation (NAT), network automation basics, basic OSPF, Quality of Service (QoS) and security threat.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
CCNA: Enterprise Networking, Security, and Automation (*) | Cisco | Dynamic Routing, Network Address Translation (NAT), Network Automation Basics, Basic OSPF, Quality of Service (QoS), Security Threat Mitigation, Software Driven Networks, Virtualization, Wide Area Networks |
CCNA: Introduction to Networks (*) |
Cisco | Ethernet, IP connectivity, IP services, IP Subnetting, IPv4 And IPv6, Addressing, Network Fundamentals, Security Fundamentals, Switching |
CCNA: Switching, Routing, and Wireless Essentials (*) | Cisco | Access Connectivity, Access Security, First-hop Redundancy, High Availability, IP services, Routing Switching Protocols, Wireless LAN Controllers |
Implementing and Administering Cisco Solutions | CCNA FEE |
Cisco | Install, operate, configure, and verify basic IPv4 and IPv6 networks; Configure network components such as switches, routers, and wireless LAN controllers; Manage network devices and identify basic security threats; How to describe and define network programmability, automation, and software-defined networking. |
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(*) Instructor-led courses are free for Academic Institutions. These Institutions may charge fees for Instructor-led classes.
For any Network and IT Automation Engineer professional hoping to achieve fluency on principal skills like application deployment, applications, application security, automation, network programming, REST, Python programming, machine learning, retrieval augmented generation and large language models.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
DevNet Associate (*) | Cisco | Application Deployment, Applications, Application Security, Automation, Cisco Platforms Cisco Development, Cloud, DevOps, DevOps Engineer, Infrastructure and Automation, IoT, JSON, Network Infrastructure, Python, Software Design, Software Development |
Introduction to Retrieval Augmented Generation (RAG) | Cisco U | Retrieval-augmented Generation |
Sorry, no results matched your search criteria(s). Please try again.
(*) Instructor-led courses are free for Academic Institutions. These Institutions may charge fees for Instructor-led classes.
For any Network and IT Automation Engineer professional hoping to achieve fluency on principal skills like application deployment, applications, application security, automation, network programming, REST, Python programming, machine learning, retrieval augmented generation and large language models.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Customer Service | IBM | Customer engagement, problem solving and process controls |
Network Technician Career path | Cisco | Application Layer Services, IPv4 Addresses, Network Media, Network Types, Protocols Standards, Wireless Access, ARP, Binary Systems, Cisco Devices, Cisco IOS, DHCP, DNS, Ethernet Operates, Hierarchical Network Design, IPv4 Subnetting, Network Layer Protocols, Transport Layer Protocols, Virtualization and Cloud Services, Troubleshooting, IPv6 Addressing, Copper and Fiber cabling, Cisco Routers, Cisco Switches, Network Troubleshooting, Support, Endpoint Devices, Network Troubleshooting, Documentation, Help Desk, User support |
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For any Senior Network Engineer professional hoping to achieve fluency on principal skills like network engineering, firewall, network management, network troubleshooting, network performance management, automation, Python (Programming Language), scripting, AI/ML for networking, data analytics, network telemetry, network security, network monitoring, SD-WAN, network quality of service (QoS), sustainability practices, SASE (Secure Access Service Edge), cloud-native security, digital experience assurance and sustainability metrics.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Cisco Enterprise Network Core Technologies FEE |
Cisco | Network Engineering, Firewall, Network Management, Network Troubleshooting |
Designing Cisco Enterprise Networks FEE |
Cisco | Network Infrastructure, Routing Protocols, Network Architecture |
Designing and Implementing Cloud Connectivity FEE |
Cisco | Network Security, Network Monitoring, SD-WAN, Network Quality of Service (QoS), Sustainability Practices, SASE (Secure Access Service Edge), Cloud-Native Security, Digital Experience Assurance, Sustainability Metrics |
Implement Automation for Cisco Enterprise Solutions FEE |
Cisco | Network Performance Management, Automation, Python (Programming Language), Scripting, AI/ML for Networking, Data Analytics, Network Telemetry |
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Access management (AD, etc.), cloud services, configuration management, cyber security, disaster recovery, scripting, technical support and virtualization.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Cybersecurity Essentials | Cisco | Cybersecurity literacy, Asset protection, Security response, Network protection, Product expertise, Data breach analysis, Data defense, Cybersecurity policies |
Cybersecurity Fundamentals | IBM | Cybersecurity literacy, Cryptography, Cyber Attacks, Cyber threat analysis, Cyber threat analysis intelligence, Cybersecurity risk management |
Network and System Administration Online Training Courses | Azure Administration, Server Administration, Network Routing, Jira, Backup and Recovery, IT Architecture | |
Network Technician Career path | Cisco | System Administration, Operating Systems (Linux, Windows 10), Local Area Networks (LANs), TCP/IP, Technical Support, Cybersecurity |
Python 3 for Scripting for System Administrators FEE |
Pluralsight | Scripting (Python), System Administration, Technical Support |
System Administration and IT Infrastructure Service | Google / Coursera | System Administration, Operating Systems, Local Area Networks, Virtualization, Backup Devices, Disaster Recovery, Access Management, Technical Support, Cloud Service, Configuration Management |
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For any Systems Analyst professional hoping to achieve fluency on principal skills like Vertex AI machine learning services, MLOps, Data Management, GitHub Copilot, debugging and issue resolution strategies, collaborative development for remote teams, documentation techniques, and more.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI and Developer Productivity FEE |
Learn how to upskill and become an AI-powered developer to remain competitive and innovative in the industry. This course covers the following concepts and provides hands-on examples and demos along the way: the role of AI in development, how to effectively use prompts, code optimization, automated testing and quality assurance, intelligent debugging and issue resolution strategies, collaborative development for remote teams, documentation techniques, interview preparation, and more. | |
AI Powered Programming with GitHub CoPilot FEE |
In this course, technical trainer and content developer Tim Warner provides comprehensive coverage of GitHub Copilot's capabilities. After a chance to brush up on basics, build your understanding of Copilot and how you can integrate it with your IDE. Learn how to apply GitHub Copilot in coding and enhance your coding with comment-based generation. Find out how to leverage Copilot in your unit testing. Plus, discover how to use GitHub Copilot to build and deploy an app. | |
Data Engineering Pipeline Management with Apache Airflow FEE |
In this course, certified Google cloud architect and data engineer Janani Ravi guides you through using Apache Airflow to complete your data engineering pipeline management workflows. Learn how to work with role-based access control, including creating users with different roles, executing a branching DAG and a SQL DAG, recalling actions that users with different roles can perform, and more. Go over how to manage SLAs and schedule DAGs with datasets. Find out how to work with AirFlow plugins and explore the CSV reader plugin. Plus, discover how to scale Apache Airflow, set up a data transformation pipeline, execute tasks, and more. | |
Data Management with Apache NiFi FEE |
If you are a data management professional, this course can give you the understanding you need to get started with this powerful tool. Janani Ravi guides you through getting started with Apache NiFi. Learn about core concepts and architecture, as well as how to download, start, and log into Apache NiFi on both macOS and Windows. Find out how to build and run data flows and how to integrate NiFi with PostgreSQL. Explore ways to configure and use NiFi processors and processing groups and integrate NiFi with Amazon S3. Plus, discover advanced features of NiFi dataflows like configuring back pressure, using a funnel in the dataflow, setting up monitoring and configuring alerts for a dataflow, and much more. | |
Google Cloud Platform for Machine Learning | In this course with instructor Lynn Langit, learn to use machine learning model development tools and services available in Google Cloud. Lynn shows how you can use Vertex AI machine learning services to develop, train, evaluate and host custom machine learning models. Learn how you can bring your own models or use the recently released generative AI foundational models as a basis for your work. Discover how new tools like Google AI Studio can get you up and running quickly and see how to use the Vertex AI APIs to master end-to-end MLOps. |
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For any Software Development professional hoping to achieve fluency in skills that are common and essential across the 15 ICT jobs under the Software Development job family: AI literacy, AI technologies, agile thinking, agile methodologies, creative thinking, critical thinking, communication, data analytics, ethical and Responsible AI, Object-Oriented Programming, Programming Foundations, Programming Languages, Software Design, Software Design Patterns, Software Development Tools, Software Testing, problem solving, solutioning, stakeholder engagement, prompt engineering, project management, System architecture and Version Control.
Essential common foundational skills needs across ICT job roles under the Data Science family for AI preparedness
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Agile Explorer | IBM | Agile thinking, Agile methodologies |
AI Canon | AI Canon | AI literacy |
AI Ecosystem overview | DIGITALEUROPE | AI ecosystem analysis, Understanding AI infrastructure, AI governance and regulation knowledge, Evaluating AI tools and platforms, Ethical AI decision-making |
AI Essentials Course | AI literacy | |
AI Ethics | IBM | Ethical and Responsible AI, AI ethics and governance |
AI for Everyone by Andrew Ng | Coursera | AI literacy |
AI Fundamentals | IBM | AI Fundamentals |
Building AI Literacy FEE |
AI literacy | |
Building Career Agility and Resilience in the Age of AI | AI technologies skills to develop a "future-proof career mindset" | |
Develop Your Prompt Engineering Skills | Prompt engineering | |
Engaging Stakeholders for Success | Cisco | Communication, Stakeholder engagement, Change Management |
Enterprise Design Thinking Co-Creator | IBM | Design Thinking, creativity, innovation |
Enterprise Design Thinking Practitioner | IBM | Design Thinking, creativity, innovation |
Explore Emerging Tech | IBM | Artificial intelligence, data, blockchain, cloud, cybersecurity, iot |
Foundations of Project Management | Google / Coursera | Project management |
Introduction to Artificial Intelligence | DIGITALEUROPE | Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Data Science Fundamentals, AI Ethics and Governance |
Introduction to modern AI | Cisco | AI literacy |
Introduction to Prompt Engineering | IBM / EDX | Prompt engineering |
Introduction to Responsible AI Skills | Cisco / Intel | Ethical and Responsible AI, AI ethics and governance |
Responsible AI Foundations | Ethical and Responsible AI, AI ethics and governance | |
Software Development Training Courses | LinkedIn |
Object-Oriented Programming, Programming Foundations, Programming Languages, Software Design, Software Design Patterns, Software Development Tools, System architecture, Software Testing, Version Control |
Working in a Digital World: Professional Skills | IBM | Agile methodologies, business acumen, creative thinking, critical thinking, communication, problem solving, solutioning |
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For any AI / ML Engineer professional hoping to achieve fluency on principal skills like algorithm, artificial Intelligence, big data, data analysis, data science, data pipelines, machine learning, Python, operations and version control.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Google LLMOps | Google / DeepLearning.AI | Operations, Version Control, Data Pipelines, Big Data |
IBM AI Engineering Professional Certificate | IBM / Coursera | Machine Learning, Artificial Intelligence, Algorithm, Python, Data Science, Data Visualization, Big Data |
IBM Python for Applied Data Science and AI | IBM / Coursera | Python, Data Analysis, Data Science, Numpy, Pandas |
Machine Learning Specialization | Stanford / DeepLearning.AI | Machine learning, Artificial Intelligence |
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For any Application Developer professional hoping to achieve fluency on principal skills like Machine learning, Artificial Intelligence, Software development, Testing and troubleshooting, System integration and Software architecture design.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Azure OpenAI: Generative AI Models and How to Use Them | In this course, instructor Sammy Deprez introduces you to Azure OpenAI services and dives into the models that are available, including GPT models, embedding models, codex models, and DALL-E models. Sammy explains what each model type is and how it works, and he offers recommendations on the best way to use it. Plus, he discusses copyright issues and goes over how to combine models and start building your own solutions. | |
Building Generative AI Skills for Developers | Generative AI has created an influx of new skills and tools for developers to leverage in their everyday work. In this learning path, you'll explore the new AI tools and frameworks that empower developers to build faster and more easily, and with the power of AI. | |
Machine Learning with Python Foundations | In this course, Frederick Nwanganga introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via the most in-demand language in use today, Python. Frederick starts with exactly what it means for machines to learn and the different ways they learn, then gets into how to collect, understand, and prepare data for machine learning. He also provides guided examples of how to accomplish each step using Python. Finally, he brings it all together to build, evaluate, and interpret the results of a machine learning model in Python. | |
Training Neural Networks in Python | This course by Eduardo Corpeño teaches the inner workings of neural networks in Python, allowing you to fully understand the algorithms behind them. Although there are professional tools that allow you to train neural networks from a high-level perspective, this course gives you a chance to tap into the details of the algorithms behind neural networks. Through exercises and examples, learn how to relate biological neurons to Python elements to build and train your own networks, and gain knowledge that can help you choose the right neural network architecture and training method for your projects and problems you encounter. |
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For any Back-End Developer professional hoping to achieve fluency on principal skills like machine learning, Back-End applications, Python programming, neural networks, PostgreSQL, Django (Web Framework), MongoDB, Docker Products, Flask, Representational State Transfer (REST), Object Relational Mapping (ORM), Observability, and Relational Database (RDBMS).
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Building Generative AI Skills for Developers | Generative AI has created an influx of new skills and tools for developers to leverage in their everyday work. In this learning path, you'll explore the new AI tools and frameworks that empower developers to build faster and more easily, and with the power of AI. | |
IBM Back-End Development Professional Certificate FEE |
IBM / Coursera | Django (Web Framework), Mongodb, Docker, Flask, Representational State Transfer (REST), Object Relational Mapping (ORM), Relational Database (RDBMS), SQL, Back-End Applications, Observability |
Machine Learning with Python Foundations | In this course, Frederick Nwanganga introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via the most in-demand language in use today, Python. Frederick starts with exactly what it means for machines to learn and the different ways they learn, then gets into how to collect, understand, and prepare data for machine learning. He also provides guided examples of how to accomplish each step using Python. Finally, he brings it all together to build, evaluate, and interpret the results of a machine learning model in Python. | |
SQL Server Machine Learning Services with Python | Learn how to analyze SQL Server data with Python. Database expert Adam Wilbert shows how to use a powerful combination of tools, including high-performance Python libraries and the Machine Learning Services add-on, directly inside SQL Server to streamline analysis. Adam shows how to use Python scripts to perform statistical analysis, generate graphics such as scatterplots and bar charts, and process tabular data. He also explains how to turn a Python script into a stored procedure and set up standalone ML services to execute scripts without impacting SQL Server performance. | |
Training Neural Networks in Python | This course by Eduardo Corpeño teaches the inner workings of neural networks in Python, allowing you to fully understand the algorithms behind them. Although there are professional tools that allow you to train neural networks from a high-level perspective, this course gives you a chance to tap into the details of the algorithms behind neural networks. Through exercises and examples, learn how to relate biological neurons to Python elements to build and train your own networks, and gain knowledge that can help you choose the right neural network architecture and training method for your projects and problems you encounter. |
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For any Cloud Engineer professional hoping to achieve fluency on principal skills like AWS, Google Cloud, Cloud compute, Microsoft Azure and MLOps.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI Powered Programming with GitHub CoPilot FEE |
In this course, technical trainer and content developer Tim Warner provides comprehensive coverage of GitHub Copilot's capabilities. After a chance to brush up on basics, build your understanding of Copilot and how you can integrate it with your IDE. Learn how to apply GitHub Copilot in coding and enhance your coding with comment-based generation. Find out how to leverage Copilot in your unit testing. Plus, discover how to use GitHub Copilot to build and deploy an app. | |
Google Cloud Platform for Machine Learning | In this course with instructor Lynn Langit, learn to use machine learning model development tools and services available in Google Cloud. Lynn shows how you can use Vertex AI machine learning services to develop, train, evaluate and host custom machine learning models. Learn how you can bring your own models or use the recently released generative AI foundational models as a basis for your work. Discover how new tools like Google AI Studio can get you up and running quickly and see how to use the Vertex AI APIs to master end-to-end MLOps. | |
Prepare for the AWS Certified Machine Learning - Specialty (MLS-C01) Exam | This learning path is for anyone looking to earn their AWS Certified Machine Learning - Specialty certification. Earning this certification validates expertise in building, training, tuning, and deploying machine learning models on AWS. To learn more about this certification, visit Amazon's website. Understand the skills and technologies to earn your MLS-C01 certification. Expand knowledge of machine learning. Learn concepts applicable to the certification. | |
Prepare for the Google Cloud Professional Machine Learning Engineer Certification | Those who have earned their Google Cloud Professional Machine Learning Engineer certification have shown their ability to design, build, and deploy machine learning models on the Google Cloud Platform. The courses in this learning path map to the skills and technologies for this certification exam. For more information, visit the Google website. Identify machine learning solutions for business problems. Demonstrate your ability to manage machine learning models. Study for the official Google certification exam. | |
Securing the Use of Generative AI in Your Organization | This course with instructor Jerich Beason seeks to equip you with the knowledge and skills to navigate the evolving landscape of AI security, enabling you to confidently leverage generative AI while mitigating risks, safeguarding sensitive information, and fortifying their organization's digital resilience. Learn about the cybersecurity risks of generative AI, how to implement effective governance, risk, and compliance (GRC) processes for LLMs, the fundamentals for detecting and mitigating attacks on generative AI, and the ethical considerations of generative AI. Jerich ends the course with a look at some important AI security strategies and frameworks. |
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For any Front-End Developer professional hoping to achieve fluency on principal skills like GPT models, JavaScript, HTML5, Microsoft Azure, React.js and apply GitHub Copilot in coding and enhance your coding with comment-based generation.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI Powered Programming with GitHub CoPilot FEE |
In this course, technical trainer and content developer Tim Warner provides comprehensive coverage of GitHub Copilot's capabilities. After a chance to brush up on basics, build your understanding of Copilot and how you can integrate it with your IDE. Learn how to apply GitHub Copilot in coding and enhance your coding with comment-based generation. Find out how to leverage Copilot in your unit testing. Plus, discover how to use GitHub Copilot to build and deploy an app. | |
Azure OpenAI: Generative AI Models and How to Use Them (1 hr, 7 languages) | In this course, instructor Sammy Deprez introduces you to Azure OpenAI services and dives into the models that are available, including GPT models, embedding models, codex models, and DALL-E models. Sammy explains what each model type is and how it works, and he offers recommendations on the best way to use it. Plus, he discusses copyright issues and goes over how to combine models and start building your own solutions. | |
Build a JavaScript AI App with React and the OpenAI API FEE |
In this course, learn how to integrate the OpenAI API into a JavaScript-based web app. Join instructor Morten Rand-Hendriksen as he takes a React-based weather app, adds a heavy dose of AI, and creates an interactive experience that knows what location you want weather information from, explains the weather data in simple language, and even suggests what to wear. Through this project-based course, Morten teaches you about API integration, user-based authentication, storing user tokens in a ServiceWorker, task-based API configuration, and sending and receiving requests to the API. | |
Building Generative AI Skills for Developers (13 hrs, 7 languages) | Generative AI has created an influx of new skills and tools for developers to leverage in their everyday work. In this learning path, you'll explore the new AI tools and frameworks that empower developers to build faster and more easily, and with the power of AI. | |
IBM Front-End Developer Professional Certificate | IBM / Coursera | Continuous Integration, Continuous Delivery, Mongodb, agile, Devops, Software Development, React (Web Framework), Front-end Development, Front-end design, Web Development, JavaScript, Web |
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For any Full-Stack Developer professional hoping to achieve fluency on principal skills like GPT models, JavaScript, HTML5, Microsoft Azure, Python, and React.js.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Azure OpenAI: Generative AI Models and How to Use Them | In this course, instructor Sammy Deprez introduces you to Azure OpenAI services and dives into the models that are available, including GPT models, embedding models, codex models, and DALL-E models. Sammy explains what each model type is and how it works, and he offers recommendations on the best way to use it. Plus, he discusses copyright issues and goes over how to combine models and start building your own solutions. | |
Building Generative AI Skills for Developers | Generative AI has created an influx of new skills and tools for developers to leverage in their everyday work. In this learning path, you'll explore the new AI tools and frameworks that empower developers to build faster and more easily, and with the power of AI. | |
Machine Learning with Python Foundations | In this course, Frederick Nwanganga introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via the most in-demand language in use today, Python. Frederick starts with exactly what it means for machines to learn and the different ways they learn, then gets into how to collect, understand, and prepare data for machine learning. He also provides guided examples of how to accomplish each step using Python. Finally, he brings it all together to build, evaluate, and interpret the results of a machine learning model in Python. | |
SQL Server Machine Learning Services with Python | Learn how to analyze SQL Server data with Python. Database expert Adam Wilbert shows how to use a powerful combination of tools, including high-performance Python libraries and the Machine Learning Services add-on, directly inside SQL Server to streamline analysis. Adam shows how to use Python scripts to perform statistical analysis, generate graphics such as scatterplots and bar charts, and process tabular data. He also explains how to turn a Python script into a stored procedure and set up standalone ML services to execute scripts without impacting SQL Server performance. | |
Training Neural Networks in Python | This course by Eduardo Corpeño teaches the inner workings of neural networks in Python, allowing you to fully understand the algorithms behind them. Although there are professional tools that allow you to train neural networks from a high-level perspective, this course gives you a chance to tap into the details of the algorithms behind neural networks. Through exercises and examples, learn how to relate biological neurons to Python elements to build and train your own networks, and gain knowledge that can help you choose the right neural network architecture and training method for your projects and problems you encounter. |
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For any Java Developer professional hoping to achieve fluency on principal skills like machine learning, Python programming, JavaScript and Web development.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Azure OpenAI: Generative AI Models and How to Use Them | In this course, instructor Sammy Deprez introduces you to Azure OpenAI services and dives into the models that are available, including GPT models, embedding models, codex models, and DALL-E models. Sammy explains what each model type is and how it works, and he offers recommendations on the best way to use it. Plus, he discusses copyright issues and goes over how to combine models and start building your own solutions. | |
Building Generative AI Skills for Developers | Generative AI has created an influx of new skills and tools for developers to leverage in their everyday work. In this learning path, you'll explore the new AI tools and frameworks that empower developers to build faster and more easily, and with the power of AI | |
Java Cloud certification FEE |
Oracle University | Java |
Java Explorer | Oracle University | An Overview of Java, Text and Numbers in Java, Arrays, Conditions, and Loops, Classes and Objects, Exception Handling, Inheritance and Interfaces and Java on OCI |
Machine Learning with Python Foundations | In this course, Frederick Nwanganga introduces machine learning in an approachable way and provides step-by-step guidance on how to get started with machine learning via the most in-demand language in use today, Python. Frederick starts with exactly what it means for machines to learn and the different ways they learn, then gets into how to collect, understand, and prepare data for machine learning. He also provides guided examples of how to accomplish each step using Python. Finally, he brings it all together to build, evaluate, and interpret the results of a machine learning model in Python. | |
Web Development | IBM | Write well-designed, testable, efficient code, integrate data from back-end services, APIs, and databases, create websites using HTML/CSS/JavaScript as well as frameworks and libraries, gather and refine specifications and requirements based on technical needs from stakeholders |
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For any Principal Software Engineer professional hoping to achieve fluency on principal skills like application development, Artificial Intelligence (AI), CI/CD, C++ Programming, Cloud computing, Flask, security, Software testing, test automation and Web application.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI Security Nuggets | Cisco | AI regulations, AI threat modeling, AI supply chain, Retrieval Augmented Generation (RAG), LLM stack |
CPA: Programming Essentials in C++ (*) | Cisco | C++ |
IBM DevOps and Software Engineering Professional Certificate | IBM / Coursera | Python Programming, Application development, Web Application, Flask, Artificial Intelligence (AI), CI/CD, Microservices, Cloud Computing, Kubernetes, Devops, Software Testing, Test-Driven Development |
Project Management Certificate | Google / Coursera | Agile Management, Change Management, Data analysis, Project management, Project planning and developing, Problem Solving and Project risk management, Strategic thinking |
Securing the Use of Generative AI in Your Organization | This course with instructor Jerich Beason seeks to equip you with the knowledge and skills to navigate the evolving landscape of AI security, enabling you to confidently leverage generative AI while mitigating risks, safeguarding sensitive information, and fortifying their organization's digital resilience. Learn about the cybersecurity risks of generative AI, how to implement effective governance, risk, and compliance (GRC) processes for LLMs, the fundamentals for detecting and mitigating attacks on generative AI, and the ethical considerations of generative AI. Jerich ends the course with a look at some important AI security strategies and frameworks. | |
Software Testing and Automation Specialization | University of Minnesota / Coursera | Test Automation, Unit Testing, Testing Automation, Static Analysis, White-box Testing Techniques, Black-box Testing Techniques |
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(*) Instructor-led courses are free for Academic Institutions. These Institutions may charge fees for Instructor-led classes.
For any Python Developer professional hoping to achieve fluency on principal skills like Algorithmic Thinking, Analytical Thinking, Basic Python Programming, Best Practices in Programming, Computer Programming Design, Develop, Debug, Scripts and Procedural Programming.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI Powered Programming with GitHub CoPilot FEE |
In this course, technical trainer and content developer Tim Warner provides comprehensive coverage of GitHub Copilot's capabilities. After a chance to brush up on basics, build your understanding of Copilot and how you can integrate it with your IDE. Learn how to apply GitHub Copilot in coding and enhance your coding with comment-based generation. Find out how to leverage Copilot in your unit testing. Plus, discover how to use GitHub Copilot to build and deploy an app. | |
IT Automation with Python | Google / Coursera | Configuration Management, Python Programming, Using Version Control, Troubleshooting & Debugging, Automation. |
Python Essentials 1 | OpenEDG / Cisco | Algorithmic Thinking, Analytical Thinking, Basic Python Programming, Best Practices in Programming, Computer Programming Design, Develop, Debug, Scripts, Procedural Programming |
Python Essentials 2 | OpenEDG / Cisco | Classes, Exceptions, Generators, Inheritance, Iterators, Methods, Modules, Object Oriented Programming, Objects, Packages, PIP, Polymorphism, Properties |
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For any Software Architect professional hoping to achieve fluency on principal skills like prompt engineer, code review, Machine Learning and software debug.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI and Developer Productivity FEE |
Learn how to upskill and become an AI-powered developer to remain competitive and innovative in the industry. This course covers the following concepts and provides hands-on examples and demos along the way: the role of AI in development, how to effectively use prompts, code optimization, automated testing and quality assurance, intelligent debugging and issue resolution strategies, collaborative development for remote teams, documentation techniques, interview preparation, and more. | |
ChatGPT Prompt Engineering for Developers | DeepLearning.AI | Prompt Engineer, Code Review, Software Debug |
Machine Learning Specialization | Stanford / DeepLearning.AI | Logistic regression, Artificial Neural Network, Linear Regression, Decision Trees |
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For any Software Developer Engineer professional hoping to achieve fluency on principal skills like code review, compliant Development, DevSecOps, prompt engineer, security, software debug, software test engineering and test execution, and secure code development.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI and Developer Productivity FEE |
Learn how to upskill and become an AI-powered developer to remain competitive and innovative in the industry. This course covers the following concepts and provides hands-on examples and demos along the way: the role of AI in development, how to effectively use prompts, code optimization, automated testing and quality assurance, intelligent debugging and issue resolution strategies, collaborative development for remote teams, documentation techniques, interview preparation, and more. | |
AI Powered Programming with GitHub CoPilot FEE |
In this course, technical trainer and content developer Tim Warner provides comprehensive coverage of GitHub Copilot’s capabilities. After a chance to brush up on basics, build your understanding of Copilot and how you can integrate it with your IDE. Learn how to apply GitHub Copilot in coding and enhance your coding with comment-based generation. Find out how to leverage Copilot in your unit testing. Plus, discover how to use GitHub Copilot to build and deploy an app. | |
ChatGPT Prompt Engineering for Developers | DeepLearning.AI | Prompt Engineer, Code Review, Software Debug |
IBM DevOps and Software Engineering Professional Certificate | IBM / Coursera | Python Programming, Application development, Web Application, Flask, Artificial Intelligence (AI), CI/CD, Microservices, Cloud Computing, Kubernetes, Devops, Software Testing, Test-Driven Development |
Machine Learning Specialization | Stanford / DeepLearning.AI | Logistic regression, Artificial Neural Network, Linear Regression, Decision Trees |
Securing the Use of Generative AI in Your Organization | This course with instructor Jerich Beason seeks to equip you with the knowledge and skills to navigate the evolving landscape of AI security, enabling you to confidently leverage generative AI while mitigating risks, safeguarding sensitive information, and fortifying their organization's digital resilience. Learn about the cybersecurity risks of generative AI, how to implement effective governance, risk, and compliance (GRC) processes for LLMs, the fundamentals for detecting and mitigating attacks on generative AI, and the ethical considerations of generative AI. Jerich ends the course with a look at some important AI security strategies and frameworks. |
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For any Senior Software Development Engineer professional hoping to achieve fluency on principal skills like Prompt Engineer, Code Review, Software Debug, Artificial Neural Network, Python Programming, Application development, Artificial Intelligence (AI), CI/CD, Microservices, Cloud Computing, Kubernetes, Devops, Software Testing and Test-Driven Development.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI and Developer Productivity FEE |
Learn how to upskill and become an AI-powered developer to remain competitive and innovative in the industry. This course covers the following concepts and provides hands-on examples and demos along the way: the role of AI in development, how to effectively use prompts, code optimization, automated testing and quality assurance, intelligent debugging and issue resolution strategies, collaborative development for remote teams, documentation techniques, interview preparation, and more. | |
ChatGPT Prompt Engineering for Developers FEE |
DeepLearning.A | Prompt Engineer, Code Review, Software Debug |
CPA: Programming Essentials in C++ (*) | Cisco | C++ |
IBM DevOps and Software Engineering Professional Certificate | IBM / Coursera | Python Programming, Application development, Web Application, Flask, Artificial Intelligence (AI), CI/CD, Microservices, Cloud Computing, Kubernetes, Devops, Software Testing, Test-Driven Development |
Machine Learning Specialization | Stanford / DeepLearning.AI | Logistic regression, Artificial Neural Network, Linear Regression, Decision Trees |
Preparing for Google Cloud Certification: Cloud DevOps Engineer Professional Certificate FEE |
Google / Coursera | SRE Culture, Business Value, Organizational Culture, Google Compute Engine, Google App Engine (GAE), Google Cloud Platform, Cloud Computing, Continuous Delivery, Kubernetes, Jenkins (Software) |
Project Management Certificate | Google / Coursera | Agile Management, Change Management, Data analysis, Project management, Project planning and developing, Problem Solving and Project risk management, Strategic thinking |
Software Testing and Automation Specialization | University of Minnesota / Coursera | Test Automation, Unit Testing, Testing Automation, Static Analysis, White-box Testing Techniques, Black-box Testing Techniques |
Sorry, no results matched your search criteria(s). Please try again.
(*) Instructor-led courses are free for Academic Institutions. These Institutions may charge fees for Instructor-led classes.
For any Software Engineer professional hoping to achieve fluency on principal skills like back-end development for websites, consuming APIs, Front-end development for website (HTML5, CSS, JavaScript), Devops, GitHub and version control, Prompt Engineer, Software debug, Software test engineering and test execution.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI Powered Programming with GitHub CoPilot FEE |
In this course, technical trainer and content developer Tim Warner provides comprehensive coverage of GitHub Copilot's capabilities. After a chance to brush up on basics, build your understanding of Copilot and how you can integrate it with your IDE. Learn how to apply GitHub Copilot in coding and enhance your coding with comment-based generation. Find out how to leverage Copilot in your unit testing. Plus, discover how to use GitHub Copilot to build and deploy an app. | |
Back-End Development Professional Certificate FEE |
IBM / Coursera | Django (Web Framework), Mongodb, Docker, Flask, Representational State Transfer (REST), Object Relational Mapping (ORM), Relational Database (RDBMS), SQL, Back-End Applications, Observability |
ChatGPT Prompt Engineering for Developers | DeepLearning.AI | Prompt Engineer, Code Review, Software Debug |
Front-End Developer Professional Certificate | IBM / Coursera | Web development, HTML, CSS, Programming with JavaScript, Developing web pages with JavaScript |
IBM DevOps and Software Engineering Professional Certificate | IBM / Coursera | Python Programming, Application development, Web Application, Flask, Artificial Intelligence (AI), CI/CD, Microservices, Cloud Computing, Kubernetes, Devops, Software Testing, Test-Driven Development |
Web Development | IBM | Write well-designed, testable, efficient code, integrate data from back-end services, APIs, and databases, create websites using HTML/CSS/JavaScript as well as frameworks and libraries, gather and refine specifications and requirements based on technical needs from stakeholders |
Sorry, no results matched your search criteria(s). Please try again.
For any Senior Software Engineer professional hoping to achieve fluency on principal skills like Cloud Computing, Code Review, Mongodb, Prompt Engineer, Software Debug and project management.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI and Developer Productivity FEE |
Learn how to upskill and become an AI-powered developer to remain competitive and innovative in the industry. This course covers the following concepts and provides hands-on examples and demos along the way: the role of AI in development, how to effectively use prompts, code optimization, automated testing and quality assurance, intelligent debugging and issue resolution strategies, collaborative development for remote teams, documentation techniques, interview preparation, and more. | |
AI Powered Programming with GitHub CoPilot FEE |
In this course, technical trainer and content developer Tim Warner provides comprehensive coverage of GitHub Copilot's capabilities. After a chance to brush up on basics, build your understanding of Copilot and how you can integrate it with your IDE. Learn how to apply GitHub Copilot in coding and enhance your coding with comment-based generation. Find out how to leverage Copilot in your unit testing. Plus, discover how to use GitHub Copilot to build and deploy an app. | |
ChatGPT Prompt Engineering for Developers | DeepLearning.AI | Prompt Engineer, Code Review, Software Debug |
CPA: Programming Essentials in C++ (*) | Cisco | C++ |
IBM Back-End Development Professional Certificate FEE |
IBM / Coursera | Django (Web Framework), Mongodb, Docker, Flask, Representational State Transfer (REST), Object Relational Mapping (ORM), Relational Database (RDBMS), SQL, Back-End Applications, Observability |
IBM Front-End Developer Professional Certificate | IBM / Coursera | Continuous Integration, Continuous Delivery, Mongodb, agile, Devops, Software Development, React (Web Framework), Front-end Development, Front-end design, Web Development, JavaScript, Web |
Machine Learning Specialization | Stanford / DeepLearning.AI | Logistic regression, Artificial Neural Network, Linear Regression, Decision Trees |
Preparing for Google Cloud Certification: Cloud DevOps Engineer Professional Certificate FEE |
Google / Coursera | SRE Culture, Business Value, Organizational Culture, Google Compute Engine, Google App Engine (GAE), Google Cloud Platform, Cloud Computing, Continuous Delivery, Kubernetes, Jenkins (Software) |
Project Management Certificate | Google / Coursera | Agile Management, Change Management, Data analysis, Project management, Project planning and developing, Problem Solving and Project risk management, Strategic thinking |
Software Testing and Automation Specialization | University of Minnesota / Coursera | Test Automation, Unit Testing, Testing Automation, Static Analysis, White-box Testing Techniques, Black-box Testing Techniques |
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(*) Instructor-led courses are free for Academic Institutions. These Institutions may charge fees for Instructor-led classes.
For any Web Developer professional hoping to achieve fluency on principal skills like Learning to converse with the ChatGPT UI to create fully realized web applications, web development, how to effectively use prompts, code optimization, automated testing and quality assurance.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI and Developer Productivity FEE |
Learn how to upskill and become an AI-powered developer to remain competitive and innovative in the industry. This course covers the following concepts and provides hands-on examples and demos along the way: the role of AI in development, how to effectively use prompts, code optimization, automated testing and quality assurance, intelligent debugging and issue resolution strategies, collaborative development for remote teams, documentation techniques, interview preparation, and more. | |
AI Powered Programming with GitHub CoPilot FEE |
In this course, technical trainer and content developer Tim Warner provides comprehensive coverage of GitHub Copilot's capabilities. After a chance to brush up on basics, build your understanding of Copilot and how you can integrate it with your IDE. Learn how to apply GitHub Copilot in coding and enhance your coding with comment-based generation. Find out how to leverage Copilot in your unit testing. Plus, discover how to use GitHub Copilot to build and deploy an app. | |
Building Generative AI Skills for Developers | Generative AI has created an influx of new skills and tools for developers to leverage in their everyday work. In this learning path, you'll explore the new AI tools and frameworks that empower developers to build faster and more easily, and with the power of AI. | |
ChatGPT for Web Developers | Explore the basics of how ChatGPT works and how to start using it to generate code—coding better and faster than ever before and optimizing the appearance of webpages with CSS. Learn to converse with the ChatGPT UI to create fully realized web applications using JavaScript and ReactJS. Along the way, level up your skills with the exercise challenges at the end of each section. By the end of this course, you’ll also be equipped with new skills for prompt engineering to create next-generation ChatGPT-powered applications. | |
Web Development | IBM | Write well-designed, testable, efficient code, integrate data from back-end services, APIs, and databases, create websites using HTML/CSS/JavaScript as well as frameworks and libraries, gather and refine specifications and requirements based on technical needs from stakeholders. |
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For any Testing and Quality Assurance Testing and Quality Assurance and Management job family: AI literacy, AI technologies, agile thinking, agile methodologies, creative thinking, critical thinking, communication, data analytics, ethical and Responsible AI, problem solving, solutioning, stakeholder engagement, prompt engineering and project management.
Essential common foundational skills needs across ICT job roles under the Data Science family for AI preparedness
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
Agile Explorer | IBM | Agile thinking, Agile methodologies |
AI Canon | AI Canon | AI literacy |
AI Essentials Course | AI literacy | |
AI Ethics | IBM | Ethical and Responsible AI, AI ethics and governance |
AI for Everyone by Andrew Ng | Coursera | AI literacy |
AI Fundamentals | IBM | AI Fundamentals |
Building AI Literacy FEE |
AI literacy | |
Building Career Agility and Resilience in the Age of AI | AI technologies skills to develop a "future-proof career mindset" | |
Creating Compelling Reports | Cisco | Communication, presentation |
Develop Your Prompt Engineering Skills | Prompt engineering | |
Engaging Stakeholders for Success | Cisco | Communication, Stakeholder engagement, Change Management |
Explore Emerging Tech | IBM | Artificial intelligence, data, blockchain, cloud, cybersecurity, iot |
Foundations of Project Management | Google / Coursera | Project management |
Introduction to Artificial Intelligence | DIGITALEUROPE | Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Data Science Fundamentals, AI Ethics and Governance |
Introduction to modern AI | Cisco | AI literacy |
Introduction to Prompt Engineering | IBM / EDX | Prompt engineering |
Introduction to Responsible AI Skills | Cisco / Intel | Ethical and Responsible AI, AI ethics and governance |
Responsible AI Foundations | Ethical and Responsible AI, AI ethics and governance | |
Working in a Digital World: Professional Skills | IBM | Agile methodologies, business acumen, creative thinking, critical thinking, communication, problem solving, solutioning |
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For any Quality Assurance Analyst professional hoping to achieve fluency on principal skills like AI Models, AI powered programming, Machine Learning tools, Azure AI and Generative design foundations, Prompt Engineering and Testing Automation.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI and Developer Productivity FEE |
Learn how to upskill and become an AI-powered developer to remain competitive and innovative in the industry. This course covers the following concepts and provides hands-on examples and demos along the way: the role of AI in development, how to effectively use prompts, code optimization, automated testing and quality assurance, intelligent debugging and issue resolution strategies, collaborative development for remote teams, documentation techniques, interview preparation, and more. | |
AI Powered Programming with GitHub CoPilot FEE |
In this course, technical trainer and content developer Tim Warner provides comprehensive coverage of GitHub Copilot's capabilities. After a chance to brush up on basics, build your understanding of Copilot and how you can integrate it with your IDE. Learn how to apply GitHub Copilot in coding and enhance your coding with comment-based generation. Find out how to leverage Copilot in your unit testing. Plus, discover how to use GitHub Copilot to build and deploy an app. | |
Azure OpenAI: Generative AI Models and How to Use Them (1 hr, 7 languages) | In this course, instructor Sammy Deprez introduces you to Azure OpenAI services and dives into the models that are available, including GPT models, embedding models, codex models, and DALL-E models. Sammy explains what each model type is and how it works, and he offers recommendations on the best way to use it. Plus, he discusses copyright issues and goes over how to combine models and start building your own solutions. | |
ChatGPT Prompt Engineering for Developers | DeepLearning.AI | Prompt Engineer, Code Review, Software Debug |
Project Management Certificate | Google / Coursera | Agile Management, Change Management, Data analysis, Project management, Project planning and developing, Problem Solving and Project risk management, Strategic thinking |
Securing the Use of Generative AI in Your Organization | This course with instructor Jerich Beason seeks to equip you with the knowledge and skills to navigate the evolving landscape of AI security, enabling you to confidently leverage generative AI while mitigating risks, safeguarding sensitive information, and fortifying their organization's digital resilience. Learn about the cybersecurity risks of generative AI, how to implement effective governance, risk, and compliance (GRC) processes for LLMs, the fundamentals for detecting and mitigating attacks on generative AI, and the ethical considerations of generative AI. Jerich ends the course with a look at some important AI security strategies and frameworks. | |
Software Testing and Automation Specialization | University of Minnesota / Coursera | Test Automation, Unit Testing, Testing Automation, Static Analysis, White-box Testing Techniques, Black-box Testing Techniques |
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For any Web Developer professional hoping to achieve fluency on principal skills like AI powered programming, code review, LLM Architecture, prompt engineering, software debug and software test automation.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI and Developer Productivity FEE |
Learn how to upskill and become an AI-powered developer to remain competitive and innovative in the industry. This course covers the following concepts and provides hands-on examples and demos along the way: the role of AI in development, how to effectively use prompts, code optimization, automated testing and quality assurance, intelligent debugging and issue resolution strategies, collaborative development for remote teams, documentation techniques, interview preparation, and more. | |
AI Powered Programming with GitHub CoPilot FEE |
In this course, technical trainer and content developer Tim Warner provides comprehensive coverage of GitHub Copilot's capabilities. After a chance to brush up on basics, build your understanding of Copilot and how you can integrate it with your IDE. Learn how to apply GitHub Copilot in coding and enhance your coding with comment-based generation. Find out how to leverage Copilot in your unit testing. Plus, discover how to use GitHub Copilot to build and deploy an app. | |
AI Security Nuggets | Cisco | AI regulations, AI threat modeling, AI supply chain, Retrieval Augmented Generation (RAG), LLM stack |
ChatGPT Prompt Engineering for Developers | DeepLearning.AI | Prompt Engineer, Code Review, Software Debug |
Machine Learning Specialization | Stanford / DeepLearning.AI | Logistic regression, Artificial Neural Network, Linear Regression, Decision Trees |
Securing the Use of Generative AI in Your Organization | This course with instructor Jerich Beason seeks to equip you with the knowledge and skills to navigate the evolving landscape of AI security, enabling you to confidently leverage generative AI while mitigating risks, safeguarding sensitive information, and fortifying their organization's digital resilience. Learn about the cybersecurity risks of generative AI, how to implement effective governance, risk, and compliance (GRC) processes for LLMs, the fundamentals for detecting and mitigating attacks on generative AI, and the ethical considerations of generative AI. Jerich ends the course with a look at some important AI security strategies and frameworks. | |
Software Testing and Automation Specialization | University of Minnesota / Coursera | Test Automation, Unit Testing, Testing Automation, Static Analysis, White-box Testing Techniques, Black-box Testing Techniques |
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For any Web Developer professional hoping to achieve fluency on principal skills like prompt engineering, Task Coordination, Regulatory Compliance, Microsoft Office, Project Team Management and Prioritization.
Note: Recommendations for developing job-specific skills in line with our analysis are provided directly by Consortium members or sourced from reputable organizations, including leading universities. These resources are available either for free or with an associated fee. We will update these resources regularly.
Course | Skills Developed | |
---|---|---|
AI and Developer Productivity FEE |
Learn how to upskill and become an AI-powered developer to remain competitive and innovative in the industry. This course covers the following concepts and provides hands-on examples and demos along the way: the role of AI in development, how to effectively use prompts, code optimization, automated testing and quality assurance, intelligent debugging and issue resolution strategies, collaborative development for remote teams, documentation techniques, interview preparation, and more. | |
ChatGPT Prompt Engineering for Developers | DeepLearning.AI | Prompt Engineer, Code Review, Software Debug |
Microsoft Office Online Training Courses | Microsoft Office | |
Project Manager | IBM | Project management, Project planning and developing, Problem Solving and Project risk management |
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