Introduction to Vector Databases Training

The Introduction to Vector Databases training by Multisoft Virtual Academy is designed to help learners understand one of the most important technologies powering modern AI applications. As organizations increasingly adopt Large Language Models (LLMs), recommendation engines, semantic search, generative AI, and image/audio similarity systems, vector databases have become essential for storing, indexing, and retrieving high-dimensional embeddings. This course provides a clear, practical introduction to the concepts behind vector storage, vector similarity search, embeddings, indexing structures, ANN (Approximate Nearest Neighbor) algorithms, and real-world implementation methods. Participants learn how vector databases differ from traditional relational and NoSQL systems, why they are optimized for AI workloads, and how they enable applications like RAG (Retrieval-Augmented Generation), chatbots, fraud detection, personalization engines, and content matching. The curriculum offers hands-on exploration of leading vector database technologies such as Pinecone, Weaviate, Milvus, ChromaDB, and FAISS. Learners gain step-by-step experience in embedding generation, dataset preparation, vector indexing, and performing similarity queries for different use cases.

Whether you are a developer, data scientist, AI engineer, or technology enthusiast, this course provides the foundation you need to confidently work with vector databases and build intelligent, search-driven applications. By the end of the program, you will be fully prepared to integrate vector search into real-world AI systems.