Week 12: Scientific AI Applications
AI transforming biology, chemistry, and scientific discovery
Time Estimate: 3-4 hours
Topics Covered
- Protein folding and AlphaFold
- Drug discovery and molecular generation
- AI for climate modeling
- Materials science and battery design
- Accelerating scientific discovery with AI
Featured Speaker
DM
DeepMind Team
Google DeepMind
Learn from industry leaders who are building the future of AI infrastructure and applications.
Video Resources
📹 Video content will be added here by Agent 2
Videos include keynotes, technical talks, and tutorials from industry leaders.
Reading Materials
📚 Reading list will be added here by Agent 3
Research papers, blog posts, and technical documentation.
🛠️ Hands-On Lab
Build a RAG Application
Beginner 3 hoursObjective
Create a retrieval-augmented generation system with embeddings, vector search, and LLM generation.
Prerequisites
- Python 3.8+
- Basic understanding of embeddings
- Familiarity with LLM APIs
- Google Colab free tier OK
Setup Instructions
- Install dependencies:
pip install sentence-transformers faiss-cpu langchain - Download a small document corpus (Wikipedia, arXiv papers)
- Set up OpenAI API key or use local model
Tasks
- Build document embeddings with sentence-transformers
- Create FAISS vector index for fast retrieval
- Implement retrieval component (top-k similar docs)
- Chain retrieval with LLM generation
- Compare retrieval strategies (dense vs sparse)
- Evaluate answer quality on test questions