Vector Databases for Developers: ChromaDB, Pinecone & RAG
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English (US) | Duration: 10 h | Size: 3.59 GB
Build Modern AI Applications with Vector Databases and Retrieval-Augmented Generation (RAG)
Have you ever wondered how ChatGPT, Claude, Gemini, and modern AI assistants search millions of documents and answer questions using your own data?
The answer is
Vector Databases
and
Retrieval-Augmented Generation (RAG).
In this hands-on course, you'll learn how to build AI-powered Semantic Search applications and production-ready RAG systems completely from scratch using Python.
Instead of focusing only on theory, you'll build real-world AI applications while learning the concepts behind embeddings, semantic search, vector databases, and modern AI architectures.
Throughout the course you'll work with industry-standard technologies including:
Python
OpenAI Embeddings
ChromaDB
Pinecone
LangChain
Semantic Search
Vector Search
RAG
PDF Processing
You'll begin by understanding how embeddings represent the meaning of text and why semantic search is far more powerful than traditional keyword search.
Next, you'll learn how to generate embeddings using the OpenAI API, compare vectors using cosine similarity, and build your own searchable knowledge base.
From there, you'll build a complete Semantic PDF Search Engine capable of searching documents using natural language.
You'll then extend that project into a complete Retrieval-Augmented Generation (RAG) Chatbot using LangChain and OpenAI.
The course also covers:
Document chunking
Metadata filtering
Top-K Retrieval
Prompt Engineering
Conversation History
Source Citations
ChromaDB
Pinecone
Hybrid Search
Production Best Practices
By the end of the course, you'll understand how modern AI search systems work and you'll have built portfolio-quality projects that demonstrate practical AI development skills.
Unlike many AI courses that simply explain concepts, this course emphasizes building real applications that you can extend into your own products.
Whether you're an AI developer, Python programmer, software engineer, or simply curious about Vector Databases and RAG, this course will give you practical skills that are immediately applicable in real-world projects.
Enroll today and start building intelligent AI applications with Vector Databases, Semantic Search, ChromaDB, Pinecone, LangChain, and Retrieval-Augmented Generation.
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