Data Science for Beginners: Microsoft’s Data Science for Beginners is designed for learners starting from scratch. Its 10-week curriculum includes 20 lessons covering statistics, probability, data ethics, data preparation, visualization, and analysis. Quizzes, assignments, practical exercises, and real datasets provide hands-on learning while introducing the complete data science workflow. 

Machine Learning for Beginners: Machine Learning for Beginners builds on fundamental data knowledge through a 12-week, 26-lesson curriculum. It covers regression, classification, clustering, natural language processing, time-series forecasting, and reinforcement learning. Learners also work with Python and Scikit-learn, gaining practical experience training and evaluating traditional machine learning models.

Artificial Intelligence for Beginners: Artificial Intelligence for Beginners introduces broader AI concepts through 24 lessons across 12 weeks. Topics include neural networks, computer vision, natural language processing, deep learning, symbolic AI, and reinforcement learning. Learners also encounter technologies including PyTorch, TensorFlow, transformers, embeddings, transfer learning, and generative adversarial networks.

Generative AI for Beginners: Generative AI for Beginners focuses on modern AI application development through 21 lessons. The curriculum covers prompt engineering, model selection, responsible AI, function calling, RAG, vector databases, AI agents, fine-tuning, security, small language models, and open-source models, with practical Python and TypeScript examples. 

AI Agents for Beginners: AI Agents for Beginners introduces agentic AI systems through an 18-lesson curriculum. Topics include tool use, agentic RAG, planning, memory, context engineering, multi-agent systems, MCP, computer-use agents, security, and deployment. Practical examples use technologies such as Microsoft Agent Framework and Microsoft Foundry Agent Service.

A Progression From Fundamentals to Agents: Together, these courses create a progression from data science fundamentals to machine learning, broader AI concepts, generative AI, and agentic systems. Learners can build knowledge gradually instead of jumping directly into advanced LLM applications without understanding data, models, training, evaluation, and AI fundamentals. 

Free Learning Through GitHub: The courses provide structured learning materials without requiring expensive training programs. Depending on the curriculum and exercises, learners can access lessons, quizzes, assignments, projects, and code examples. Some generative AI exercises may require access to an AI API or Microsoft Foundry, while some models can run locally. 

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