AI Engineering & Generative AI Course
Learn AI engineering with Python, LLM APIs, RAG, vector search, LangGraph, MCP and FastAPI. Build production-oriented AI agents and enterprise AI systems.
The VidhaiX AI Engineering program teaches developers how to build production-oriented generative AI applications using Python, LLM APIs, RAG, vector databases, LangGraph, MCP and FastAPI.
Who Is This Course For?
AI Engineer / GenAI Developer / Applied AI Specialist
₹12L - ₹24L CTC
Live code reviews, debugging guidance, and small learning cohorts.
How Does Mentorship Work?
Build and ship working software instead of passive video recordings.
Senior engineers inspect your Pull Requests and teach clean architectural habits.
Resume optimization, mock technical interview grilling, and direct hiring referrals.
How Does the Curriculum Work?
Structured progressive modules designed to build compounding engineering mastery.
LLM Foundations, Tokenomics & Vector Stores
Tokenomics, temperature, prompt orchestration, vector embeddings, and semantic vector stores with pgvector.
Tokenomics, temperature, prompt orchestration, vector embeddings, and semantic vector stores with pgvector.
Production RAG, Chunking & Evaluation Frameworks
Contextual chunking, hybrid search (BM25 + pgvector), semantic caching, and LLM evaluation benchmarks (Ragas).
Contextual chunking, hybrid search (BM25 + pgvector), semantic caching, and LLM evaluation benchmarks (Ragas).
Multi-Agent Architectures, Tool Use & Autonomous Capstone
LangGraph multi-agent coordination, Model Context Protocol (MCP) server design, human-in-the-loop, and autonomous capstone.
LangGraph multi-agent coordination, Model Context Protocol (MCP) server design, human-in-the-loop, and autonomous capstone.
What Projects Will You Build?
Real applications with production architectures to showcase on your GitHub profile and resume.
Enterprise Production RAG Pipeline
Hybrid semantic search with pgvector, BM25 rerankers, and contextual chunking over enterprise documentation.
Autonomous Multi-Agent Researcher
LangGraph collaborative agents executing web browsing, paper summarization, synthesis, and report generation.
Custom MCP Server Suite
Production Model Context Protocol servers exposing private enterprise databases and APIs safely to AI agents.
Frequently Asked Questions
What is AI engineering?
AI engineering is the discipline of building production software that integrates foundation models, vector search, RAG pipelines, and autonomous agents into dependable business systems.
What is RAG (Retrieval-Augmented Generation)?
RAG enables LLMs to accurately answer questions using your private enterprise documents by semantically retrieving relevant context before generating answers.
What is the Model Context Protocol (MCP)?
MCP is the open standard that connects AI assistants to external data sources, local files, and enterprise APIs.
Ready to master AI Engineering & Generative AI Course?
Speak directly with our technical admissions mentor to discuss batch timings, prerequisites, fee plans, and career placement options.