--- title: EXD β€” Self-Directed PhD in AI emoji: 🧠 colorFrom: indigo colorTo: purple sdk: static pinned: true --- # 🧠 EXD β€” Self-Directed PhD in AI **Engineering mastery through first principles, from the top down.** A deep dive into AI engineering β€” fine-tuning, architectures, inference optimization, and systems thinking. Work backwards from high-level concepts to fundamentals. --- ## πŸ—ΊοΈ Episodes | # | Title | Video | Interactive | Article | |---|-------|-------|-------------|---------| | 01 | Intro to EXD | [πŸ“Ί Watch](https://youtu.be/mUFNk2yOblc) | β€” | β€” | | 02 | Setup & First Inference | [πŸ“Ί Watch](https://youtu.be/pPboQK6hXBw) | β€” | [πŸ“– GitHub](https://github.com/Ramshreyas/EXD/blob/main/episodes/Ep02/ep2-setup-and-first-inference.md) | | 03 | Inference Benchmarking | [πŸ“Ί Watch](https://youtu.be/BwMJo25iK9A) | [πŸš€ Simulator](https://huggingface.co/spaces/EXD-AI/inference-simulator) | [πŸ“– GitHub](https://github.com/Ramshreyas/EXD/blob/main/episodes/Ep03/ep3-inference-benchmarking.md) | | 04 | Performance Tuning | [πŸ“Ί Watch](https://youtu.be/jUDci02mTOM) | [πŸš€ Sim v2](https://huggingface.co/spaces/EXD-AI/inference-simulator-v2) | [πŸ“– GitHub](https://github.com/Ramshreyas/EXD/blob/main/episodes/Ep04/ep4-inference-benchmarking-continued.md) | | 05 | Speculative Decoding | [πŸ“Ί Watch](https://youtu.be/ip8G_ukhI7E) | [⚑ Spec Decode](https://huggingface.co/spaces/EXD-AI/speculative-decoding-simulator) | [πŸ“– GitHub](https://github.com/Ramshreyas/EXD/blob/main/episodes/Ep05/shownotes.md) | | 06 | Taking Stock | [πŸ“Ί Watch](https://youtu.be/bFWP2QDxAAU) | β€” | β€” | | 07 | Tokenization & Embeddings | [πŸ“Ί Watch](https://youtu.be/E03MyfzUsJI) | [πŸ”€ Notebook](https://huggingface.co/datasets/EXD-AI/episode-07-tokenization) | [πŸ“– GitHub](https://github.com/Ramshreyas/EXD/blob/main/episodes/Ep07/tokenization_and_embeddings.ipynb) | --- ## πŸ“¦ Artifacts | Type | Name | Description | |------|------|-------------| | πŸ“Š Dataset | [benchmark-results](https://huggingface.co/datasets/EXD-AI/benchmark-results) | Performance data from inference sweeps | | βš™οΈ Dataset | [vllm-configs](https://huggingface.co/datasets/EXD-AI/vllm-configs) | Production vLLM configuration profiles | | πŸ“ Article | [GitHub episodes](https://github.com/Ramshreyas/EXD/tree/main/episodes) | Full write-ups for each episode | | πŸ““ Notebook | [episode-07-tokenization](https://huggingface.co/datasets/EXD-AI/episode-07-tokenization) | Tokenization & embeddings deep-dive | --- ## 🌐 Links πŸ“Ί [YouTube Channel](https://youtube.com/@EXD-ai) Β· πŸ’» [GitHub](https://github.com/Ramshreyas/EXD) Β· πŸ—οΈ [@EXDai](https://huggingface.co/EXDai) Β· πŸ“š [Collection](https://huggingface.co/collections/EXD-AI/EXD-AI/exd-self-directed-phd-in-ai-6a3bbd3cbac6d838d3c749e2) --- ## πŸ› οΈ Focus Areas - Model fine-tuning (LoRA, QLoRA, RLHF/DPO) - Transformer architectures (attention variants, MoE) - Inference optimization (quantization, KV cache, speculative decoding, compilation) --- *Work backwards. Understand everything.*