AI & ML
12 units to master
ML Foundations
Every ML interview starts here. Master the fundamentals that separate junior from senior candidates.
13 lessons
Deep Learning
Neural networks power modern AI. Build the foundation for understanding transformers.
13 lessons
Transformers & LLMs
Transformers changed everything. Master the architecture that powers modern AI.
13 lessons
LLM Training & Inference Internals
The full lifecycle from pre-training through post-training to inference optimization. Scaling laws, RLHF pipelines, KV caching, and prompt caching economics.
4 lessons
LLM Engineering
Building applications with LLMs is the fastest-growing area in AI. Master RAG, embeddings, and fine-tuning.
14 lessons
Evaluation & Benchmarking
You cannot improve what you cannot measure. Master evaluation frameworks, benchmarks, and testing for ML and LLM systems.
12 lessons
Chatbot Architecture & Adaptation
From prompts to production chatbots. Master system design, context engineering, adaptation strategies, and structured output.
9 lessons
RAG Engineering & RAFT
Ground LLMs in real data. Master document parsing, hybrid retrieval, RAFT, and end-to-end RAG operations.
9 lessons
Agentic AI Systems
The complete guide to building AI agents. From foundational autonomy concepts and workflow patterns to function calling, agent architectures, multi-agent coordination, reliability engineering, and computer use.
22 lessons
Reasoning Models & Deep Research
Inference-time scaling, chain-of-thought, tree of thoughts, reward modeling, and deep research pipelines.
10 lessons
Multimodal Generation
From text-to-image to text-to-video. Diffusion models, DiT architectures, evaluation metrics, and responsible generation.
9 lessons
Production Reliability, Safety & Governance
Ship ML systems that work at scale. MLOps, caching, routing, observability, prompt injection defense, and AI governance.
19 lessons