Learning AI at a Glance

What is Supervised Learning? 20 min Python Basics for AI 25 min Math & Statistics Refresher 30 min Data Wrangling Essentials 20 min Clustering and Dimensionality 25 min RL Intuition 25 min ML Workflow Overview 15 min

Neural Networks from Scratch 35 min Convolutional Neural Networks 30 min Introduction to Transformers 40 min Training Deep Models 25 min Sequence Models and RNNs 25 min Transfer Learning 20 min

Large Language Models Overview 30 min Prompt Engineering Fundamentals 25 min Fine-tuning Basics 35 min Multimodal Generation Intro 25 min Diffusion Models Basics 30 min Foundation Models Landscape 20 min Structured Outputs 15 min

Embeddings Explained 20 min Build a RAG Pipeline 40 min Vector Databases in Practice 30 min Chunking Strategies 20 min Hybrid Search 20 min Citation and Grounding 15 min

LangChain Essentials 35 min LlamaIndex Essentials 30 min Model I/O Patterns 25 min Streaming and Tool Calling 30 min Observability for Chains 20 min Prompt Templates 15 min

Agent Planning Loops 30 min Giving Agents Tools 30 min Agent Memory Systems 25 min Multi-Agent Patterns 35 min Human-in-the-Loop Agents 20 min

Evaluating LLM Apps 30 min Monitoring in Production 25 min Deploying AI Services 35 min Safety and Guardrails 25 min Cost Optimization 20 min