This guided project walks you through building a mini AI tool that can watch YouTube lectures, extract their content, summarize the key points, and generate clean notes automatically.
Perfect for beginners who want to dive into AI + NLP + automation without complex setups.
| Category | Details |
|---|---|
| Type | Guided Project |
| Difficulty | Beginner |
| Duration | 5 Weeks |
| Weekly Time | ~6 hours |
| Domains | Natural Language Processing, Agentic AI |
| Mentor | Dinesh Baghel |
- Learn to use the YouTube Transcript API to extract captions.
- Understand how to clean and structure transcript text.
- Deliverable: Extract text from any YouTube lecture and save it in
.txtformat.
- Use Hugging Face Transformers (T5, BART, Pegasus) for text summarization.
- Generate short summaries for long transcripts.
- Deliverable: Script that summarizes video transcript.
- Structure summaries into topic-wise bullet points or markdown notes.
- Add section titles intelligently (like “Introduction”, “Concept 1”, etc.)
- Create a simple Streamlit or Gradio web UI.
- Input a YouTube URL → get auto-generated notes.
- Automate summarization with batching and error handling.
- Add custom prompts for improved summaries.
- Final polishing and presentation prep.
- Language: Python
- Libraries:
youtube-transcript-api,transformers,torch,streamlit,nltk,requests - APIs: YouTube Data API, Hugging Face
- Tools: Jupyter Notebook / VS Code
- Install python and revise its basics
- Create a Github repo named "
your-roll-number-from-video-to-notes" - Keep track of each weeks progress and push everything in your Github repo