Guided tracks from fundamentals to production
The MVP uses deterministic path sequencing instead of opaque black-box recommendations.
Generative AI Foundations
A guided path from Python and ML basics into practical LLM workflows.
Professional LLM Engineer Path
Production-oriented track covering RAG, MCP, agent systems, and operations.
Machine Learning Foundations Study Guide
Foundational ML and data-science resources spanning Google, Kaggle, IBM, CS50, and fast.ai.
GenAI Essentials Study Guide
Core generative AI, prompting, and LLM foundations from Microsoft, DeepLearning.AI, Google, and AWS.
RAG and LLM Applications Study Guide
Practical application-building track for retrieval, vector search, fine-tuning, and LLM systems work.
Agents and MCP Study Guide
Agent workflows, assistant-building, MCP foundations, and Copilot extension resources grouped together.
Responsible AI and Evals Study Guide
Governance, safety, evaluation, ethics, and AI risk-management resources.
Production AI and MLOps Study Guide
Deployment, operations, analytics engineering, and production ML workflows for real systems.
Multimodal and Vision Study Guide
Vision, audio, diffusion, robotics, and reinforcement-learning resources for broader AI systems.