// the find
krishnaik06/Roadmap-To-Learn-Generative-AI-In-2025
A single README of links to Krish Naik's YouTube playlists covering Python, NLP, deep learning, and generative AI (LangChain, LLM fine-tuning, vector DBs). It's a study checklist for beginners trying to get into GenAI, not a code repository — there's no code here at all, just a LICENSE file and this list.
The topic progression is sound — Python, then classical NLP, then deep learning fundamentals (RNN/LSTM/attention) before jumping into transformers and LLMs, which is the right order for someone building real understanding instead of just copying LangChain snippets. It also covers the unglamorous parts people skip, like deployment (AWS/Azure/HuggingFace Spaces) and vector store options beyond just FAISS.
There is zero code, no notebooks, no exercises — every single line is a link out to YouTube, so the repo itself teaches nothing on its own and you're fully dependent on hours of video content staying up. Several links are duplicated or mislabeled (the AWS/Azure/Google Gemini 'Generative Tutorials' entries all point to the same LangChain docs badge), and the fine-tuning and vector DB sections are just a bullet list of names with no comparison or guidance on when to use which. The star count reflects the instructor's YouTube following more than the value of this particular document — it hasn't been meaningfully updated (still README/LICENSE/.gitignore only) despite the 2025 branding.