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16 weeks · 3 tracks · 1 goal

A shared foundation, then fork into the specialization that fits your career

schedule 16 weeks menu_book 100+ resources fork_right 3 tracks

school Core Foundation Everyone — Weeks 1–4

1

Python & Math

schedule Weeks 1–2
open_in_new Python Official Tutorial — Start from the Basics free open_in_new DeepLearning.AI: AI Python for Beginners free open_in_new Automate the Boring Stuff — Practice Projects free open_in_new 3Blue1Brown: Linear Algebra — Visual Intuition free open_in_new Khan Academy: Statistics & Probability free open_in_new Mathematics for Machine Learning — Reference Book free
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2

ML & Neural Networks

schedule Weeks 3–4
open_in_new Andrew Ng's ML Specialization — Core ML Theory freemium open_in_new Google ML Crash Course — Quick Interactive Intro free open_in_new fast.ai Practical Deep Learning — Learn by Building free open_in_new 3Blue1Brown: Neural Networks — Visual Intuition free open_in_new DeepLearning.AI: Generative AI for Everyone free open_in_new Kaggle Learn — Hands-on ML Competitions free
fork_right Choose Your Specialization
science
Track A

Applied AI Scientist

For researchers, data scientists, and model developers

Stage 5 schedule Weeks 5–6

Deep Learning Architectures

open_in_new Deep Learning Specialization — CNNs, RNNs & Optimization freemium open_in_new MIT 6.S191 — Introduction to Deep Learning free open_in_new Dive into Deep Learning — Interactive Textbook with Code free open_in_new Stanford CS231n — CNNs for Visual Recognition free open_in_new PyTorch Tutorials — Build Architectures Hands-on free
Stage 6 schedule Weeks 7–8

NLP & Transformers

open_in_new The Illustrated Transformer — Visual Guide to Attention free open_in_new Stanford CS224N — Full NLP with Deep Learning Course free open_in_new HuggingFace NLP Course — Hands-on with Transformers free open_in_new The Illustrated GPT-2 — Visualizing Language Models free open_in_new Attention Is All You Need — The Original Paper free
Stage 7 schedule Weeks 9–10

LLMs & Fine-tuning

open_in_new Karpathy: Intro to Large Language Models (1hr) free open_in_new Karpathy: Let's Build GPT from Scratch free open_in_new LLM University by Cohere — Comprehensive LLM Course free open_in_new HuggingFace PEFT & LoRA — Parameter-Efficient Fine-tuning free open_in_new DeepLearning.AI: Fine-tuning LLMs — Adapt Models free
Stage 8 schedule Weeks 11–12

Agentic AI & Autonomous Systems

open_in_new Lilian Weng: LLM Powered Agents — Concepts & Architecture free open_in_new DeepLearning.AI: Agentic Design Patterns with AutoGen free open_in_new Anthropic: Building Effective Agents — Patterns Guide free open_in_new Weights & Biases — Experiment Tracking for Research free open_in_new Papers with Code — Track State-of-the-Art Results free
Stage 9 schedule Weeks 13–14

Computer Vision & Multimodal AI

open_in_new DeepLearning.AI: CNNs — From Basics to Advanced freemium open_in_new HuggingFace: Vision Transformers (ViT) Guide free open_in_new fast.ai: Stable Diffusion from Scratch free open_in_new HuggingFace Tasks — Multimodal AI Guide free open_in_new Segment Anything (SAM) — Meta AI Vision Research free
Stage 10 schedule Weeks 15–16

Reinforcement Learning & RLHF

open_in_new HuggingFace: Deep RL Course — From Zero to Hero free open_in_new Spinning Up in Deep RL — OpenAI's Introduction free open_in_new David Silver's RL Course — Full Lecture Series free open_in_new DeepLearning.AI: RLHF — Training with Human Feedback free open_in_new InstructGPT Paper — RLHF Applied to LLMs free
dns
Track B

AI Platform Engineer

For infrastructure engineers, SREs, and DevOps building AI platforms

Stage 5 schedule Weeks 5–6

MLOps Fundamentals

open_in_new Made With ML — End-to-End MLOps from Basics free open_in_new Google: MLOps Maturity & Best Practices free open_in_new Designing ML Systems — Production Architecture paid open_in_new MLflow Tutorials — Experiment Tracking & Registry free open_in_new DVC — Data & Model Version Control free
Stage 6 schedule Weeks 7–8

LLM Serving & Inference

open_in_new HuggingFace: What is LLM Inference & How It Works free open_in_new vLLM — Paged Attention & Continuous Batching free open_in_new TensorRT-LLM — NVIDIA Optimized Inference free open_in_new Ollama — Run LLMs Locally, Learn Serving Basics free open_in_new KServe — Production Model Serving on Kubernetes free
Stage 7 schedule Weeks 9–10

Agent Infra & MCP Gateways

open_in_new Anthropic: What is MCP & Why It Matters free open_in_new MCP Specification — Build Servers & Gateways free open_in_new LangFuse — Agent Traces & Observability free open_in_new LangSmith — Debug & Monitor LLM Applications free open_in_new Portkey AI Gateway — Routing & Load Balancing free
Stage 8 schedule Weeks 11–12

Guardrails & Observability

open_in_new Guardrails AI — What Are Guardrails & Validation free open_in_new NVIDIA NeMo Guardrails — Programmable Safety free open_in_new Ray & KubeRay — Distributed AI at Scale free open_in_new Weights & Biases — Production ML Monitoring free open_in_new Evidently AI — ML Model Monitoring & Drift Detection free
Stage 9 schedule Weeks 13–14

GPU Optimization & Quantization

open_in_new NVIDIA DLI — GPU Computing Fundamentals freemium open_in_new HuggingFace: Quantization Guide — GPTQ, AWQ, GGUF free open_in_new DeepLearning.AI: Quantization Fundamentals free open_in_new llama.cpp — Efficient Local LLM Inference free open_in_new HuggingFace Optimum — Hardware-Accelerated Inference free
Stage 10 schedule Weeks 15–16

Distributed Training & Scaling

open_in_new PyTorch FSDP — Fully Sharded Data Parallel Training free open_in_new DeepSpeed — Microsoft's Large-Scale Training Library free open_in_new Megatron-LM — NVIDIA Distributed Training free open_in_new SkyPilot — Run AI Workloads Across Clouds free open_in_new Kubernetes — GPU Scheduling & Autoscaling free
terminal
Track C

AI Software Engineer

For product engineers building AI-powered applications

Stage 5 schedule Weeks 5–6

LLM APIs & Prompting

open_in_new DeepLearning.AI: Intro to Prompt Engineering free open_in_new Anthropic — Advanced Prompt Techniques free open_in_new OpenAI Cookbook — Production Code Examples free open_in_new OpenAI: Function Calling & Structured Output free open_in_new OWASP LLM Top 10 — Prompt Security free
Stage 6 schedule Weeks 7–8

RAG & Vector Databases

open_in_new Pinecone: What is RAG & How Embeddings Work free open_in_new DeepLearning.AI: Building & Evaluating RAG free open_in_new LlamaIndex — Build RAG Pipelines Step by Step free open_in_new ChromaDB — Open-Source Vector Database Tutorial free open_in_new AI Engineering by Chip Huyen — Production RAG paid
Stage 7 schedule Weeks 9–10

AI Agents, MCP & A2A

open_in_new DeepLearning.AI: What Are AI Agents — Intro Course free open_in_new LangChain — Build Agent Workflows free open_in_new LangGraph — Stateful Multi-Agent Systems free open_in_new MCP — Connect Agents to Tools & Context free open_in_new Google A2A — Multi-Agent Communication free
Stage 8 schedule Weeks 11–12

Production AI Apps

open_in_new Full Stack Deep Learning — End-to-End AI Apps free open_in_new Vercel AI SDK — Build Streaming AI Interfaces free open_in_new Streamlit — Rapid AI Prototyping free open_in_new Guardrails AI — Safety & Output Validation free open_in_new LangSmith — Monitor & Debug in Production free
Stage 9 schedule Weeks 13–14

Evaluation & Testing

open_in_new LMSYS Chatbot Arena — Understanding LLM Benchmarks free open_in_new Promptfoo — Systematic Prompt Testing free open_in_new RAGAS — RAG Evaluation Framework free open_in_new DeepEval — Open-Source LLM Testing free open_in_new OpenAI Evals — Automated LLM Evaluation free
Stage 10 schedule Weeks 15–16

Full-Stack AI & Advanced Patterns

open_in_new OpenAI: Production Best Practices free open_in_new CrewAI — Multi-Agent App Orchestration free open_in_new Haystack — Open-Source NLP Framework free open_in_new Hands-On Large Language Models (Book) paid open_in_new r/LocalLLaMA — Open-Source AI Community free
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