Overview
DeepLearning.AI's short course teaches how to create six exciting applications of vector databases and implement them using Pinecone, covering RAG, recommender systems, and advanced search techniques.
Applications Covered
- RAG for LLM Enhancement: Augment language models with external knowledge
- Recommender Systems: Combine semantic search with RAG
- Hybrid Search: Find items using both images and descriptive text
- Semantic Search: Implement efficient similarity search
- Anomaly Detection: Identify outliers in vector spaces
- Question Answering: Build intelligent Q&A systems
Technical Skills
- Implementing vector databases with Pinecone
- Building RAG pipelines
- Creating hybrid search systems
- Multimodal retrieval techniques
- Semantic similarity search
- Production deployment strategies
- Short, focused course from DeepLearning.AI
- Hands-on implementation exercises
- Real-world application examples
- Pinecone integration throughout
- Practical, project-based learning
Target Audience
- ML engineers and data scientists
- AI application developers
- Software engineers building with LLMs
- Technical professionals in AI/ML
Prerequisites
- Basic Python programming
- Understanding of machine learning concepts
- Familiarity with embeddings (helpful but not required)
Pricing
Free course from DeepLearning.AI
