Track D - Research and Foundation Model Progress Tracker

Track your progress through the universal foundation and Track D - Research and Foundation Model.

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 D - Research and Foundation Model

• [ ] Scaling Laws & Pre-training - 4h
• [ ] Distributed Training & Training Infrastructure - 4h
• [ ] Distributed Training & Training Infrastructure - 3h
• [ ] Advanced Fine-Tuning for LLM Adaptation - 4h
• [ ] Reinforcement Learning for LLM Alignment - 4h
• [ ] Knowledge Distillation & Model Compression - 3h
• [ ] Mechanistic Interpretability - 2h
• [ ] Research Methodology & Paper Reading for AI - 2h
• [ ] GPU & CUDA Programming for AI Engineers - 4h
• [ ] Reasoning Models & Test-Time Compute - 3h
• [ ] Attention Mechanism Deep Dive - 4h
• [ ] State Space Models - 3h
• [ ] Model Merging - 3h