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Introduction to Vector Databases Corporate Training is designed for professionals working with AI, machine learning, and data-driven applications. This course explains core concepts like vector embeddings, similarity search, indexing techniques, and real-world use cases. Through practical insights, learners gain the skills needed to implement vector databases for recommendation systems, semantic search, and intelligent analytics, making it ideal for enterprise and corporate teams.
The Introduction to Vector Databases training provides a foundational understanding of how vector-based storage and retrieval power modern AI applications. The program explains embeddings, similarity search, ANN indexing, and high-dimensional data handling. Learners explore popular vector databases like Pinecone, Milvus, Weaviate, Qdrant, and FAISS, while building hands-on skills to integrate vector search into LLMs, RAG systems, chatbots, and recommendation engines. This training equips professionals to design scalable, intelligent, and AI-ready data solutions.
- Understanding data dimensions
- Importance in AI and machine learning
- What are vector databases?
- Key features and benefits
- Vector databases vs traditional databases
- Types of vector data
- Basic operations on vectors
- Introduction to vector embeddings
- Simple indexing strategies
- Performing basic similarity searches
- Use cases for similarity searches
- How vector databases support AI?
- Simple AI applications using vector databases
- Future trends in vector databases
- Creating a small vector database
- Indexing and searching vector data
- Discussing real-world applications
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Introduction to Vector Databases Corporate Training Certification
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