Track C - ML and Production Engineer Progress Tracker

Track your progress through the universal foundation and Track C - ML and Production Engineer.

Level 1: Prerequisites (~15 hours)

• [ ] Python for AI - 3h
• [ ] Linear Algebra for AI - 3h
• [ ] Probability & Statistics for AI - 2h
• [ ] Neural Networks - 3h
• [ ] Deep Learning Fundamentals - 2h
• [ ] NLP Fundamentals - 2h

Level 2: GenAI Foundations (~20 hours)

• [ ] Transformers - 4h
• [ ] Attention Mechanism - 3h
• [ ] Tokenization - 2h
• [ ] Embeddings - 3h
• [ ] Modern LLM Architectures - 4h
• [ ] Scaling Laws & Pre-training - 4h

Level 3: Core GenAI Techniques (~25 hours)

• [ ] Large Language Models (LLMs) - 3h
• [ ] Prompt Engineering - 2h
• [ ] Context Engineering & Long Context - 3h
• [ ] Function Calling, Structured Output & Tool Use - 3h
• [ ] Retrieval-Augmented Generation (RAG) - 4h
• [ ] Fine-Tuning LLMs - 4h
• [ ] AI Agents - 4h
• [ ] LLM Evaluation & Benchmarks - 2h

Track C - ML and Production Engineer

• [ ] Docker & Kubernetes for GenAI Deployment - 3h
• [ ] Model Serving for LLM Applications - 3h
• [ ] Monitoring & Observability for GenAI Systems - 3h
• [ ] CI/CD for ML and LLM Systems - 3h
• [ ] Cloud ML Services & Managed AI Platforms - 3h
• [ ] ML Experiment & Data Management - 2h
• [ ] ML Experiment & Data Management - 2h
• [ ] Classical ML for GenAI Builders - 2h
• [ ] Latency & Throughput Engineering for AI Systems - 3h
• [ ] Distributed Systems Fundamentals for AI - 3h
• [ ] Distributed Inference & Serving Architecture - 3h
• [ ] Inference Optimization - 3h
• [ ] Cost Optimization for GenAI Systems - 3h