Vector Databases
If you like applying Vector Databases, every challenge here gives you a chance to practice it on a real industry brief.
- AnalysisIntermediateNew
Benchmark Approximate Nearest-Neighbor Indexes for a Code-Search Startup
You receive a 5 M-vector sample (768-dim, float32) and a 1,000-query labeled benchmark with ground-truth top-50 neighbors per query. Index the same sample in Chroma (HNSW), Qdra…
- Ann Indexes
- Hnsw
- Benchmarking
Vector Databases and Embeddings - CodeIntermediateNew
Ship an MVP RAG Knowledge Assistant for a Climate-Tech Startup
As a 4-person team across a 6-week sprint, ship: (1) an ingestion pipeline for around 4,000 mixed PDFs and markdown files; (2) a vector store with documented chunking strategy; …
- Retrieval Augmented Generation
- Software Engineering For Ai
- Vector Databases
AI Software Engineering Group Project
How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
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