Vector Database Fundamentals
About this course
Vector databases are the engines behind AI applications. Companies investing heavily in AI need expertise to build AI-powered technologies such as recommendation engines, search engine information retrieval, machine learning tasks, data analysis, semantic matching, and content generation. This ongoing growth and increasing demand for novel uses of AI-powered applications means that the need for data professionals with vector database skills will continue to grow. This Vector Database Fundamentals Specialization provides application developers, data scientists, and other AI professionals with valuable vector database skills for building real-world applications such as recommendation engines, personalized user experiences, and other new AI-powered technologies. Acquire these in-demand vector database skills in this specialization using Chroma DB, MongoDB, PostgreSQL, and Cassandra. You'll perform vector database tasks such as creating embeddings and collections, plus similarity searches, including the computation of similarity scores between query embeddings and document embeddings. You'll gain practical skills through hands-on labs. And you‘ll complete a capstone project where you’ll put your new skills into practice and incorporate RAG and LangChain to solve a real-world business problem using vector data. Great experience for interviews and your resume! Enroll today and future-proof your AI and data career with the vector database skills businesses need.
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What you'll learn
- create and manage vector embeddings
- perform similarity searches
- work with Chroma DB, MongoDB, and PostgreSQL
- execute a capstone project involving real-world vector data
Course objectives
- equip professionals with skills for AI applications
- enhance job prospects in data science and AI fields
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