Join Coding Now – Gurukul of AI. Master LLM Fine-Tuning, RAG, LangChain, AI Agents & Diffusion Models. The most comprehensive GenAI program in NSP. Batch July 2026.
Generative AI is reshaping industries. Companies need engineers who can fine-tune models, build RAG systems, and deploy autonomous agents — not just prompt users.
Uses ChatGPT, Claude, and other tools. Limited to what the UI offers. No customization.
Fine-tunes LLMs, builds RAG pipelines, orchestrates agents, deploys production systems. Builds the tools that users rely on.
Become a full-stack GenAI engineer — from model fine-tuning to production deployment.
Master LoRA, QLoRA, and instruction fine-tuning on Hugging Face. Adapt models to custom domains with minimal compute.
Build knowledge-grounded AI systems using Pinecone, Chroma, and FAISS. Implement hybrid search and reranking.
Orchestrate LLM workflows with chains, memory, and stateful graphs. Build complex, production-ready applications.
Build ReAct agents and multi-agent systems using CrewAI and LangGraph. Deploy autonomous task-execution systems.
Generate images with Stable Diffusion and DALL·E. Build multimodal apps with GPT-4o, Claude 3, and Gemini Vision.
Deploy production-ready GenAI apps with FastAPI, Docker, and cloud platforms. Master monitoring and cost optimization.
4-month intensive program at Coding Now NSP. Build 5 production-grade GenAI applications.
| Module | Topics Covered | Duration |
|---|---|---|
| Module 1 GenAI Fundamentals | Transformers, attention, foundation models, diffusion models, GANs, VAEs, RLHF | 1 Week |
| Module 2 LLM APIs & Prompt Engineering | OpenAI, Anthropic, Gemini APIs, system prompts, few-shot, chain-of-thought, structured output | 2 Weeks |
| Module 3 LLM Fine-Tuning (PEFT) | LoRA, QLoRA, instruction fine-tuning, Hugging Face Transformers, custom dataset adaptation | 2 Weeks |
| Module 4 Embeddings & Vector Databases | Semantic search, Pinecone, Chroma, FAISS, hybrid search, embedding evaluation | 2 Weeks |
| Module 5 RAG Systems | Full RAG pipeline, chunking, retrieval, generation, reranking, RAGAS evaluation | 2 Weeks |
| Module 6 LangChain & LangGraph | Chains, memory, document loaders, stateful graphs, conditional routing, human-in-the-loop | 2 Weeks |
| Module 7 Agentic AI & Multi-Agent Systems | ReAct agents, tool-use, CrewAI, AutoGen, supervisor-worker patterns, agent orchestration | 2 Weeks |
| Module 8 Diffusion Models & Multimodal AI | Stable Diffusion, DALL·E, control nets, GPT-4o Vision, Claude 3, Gemini Vision | 2 Weeks |
| Module 9 GenAI Deployment & MLOps | FastAPI, Docker, cloud deployment, token monitoring, cost optimization, observability | 2 Weeks |
| Module 10 Capstone Project | End-to-end GenAI application: LLMs, RAG, agents, diffusion, deployment with full lifecycle | 3 Weeks |
Every student builds and deploys 5 production-grade GenAI applications during the course.
Custom LLM-powered chatbot with RAG over company documents, deployed as a web app with conversation memory.
Ingest PDFs, Word docs, and web pages. Build a semantic search + LLM answer system with citation support.
Stable Diffusion pipeline with prompt engineering, control nets, and batch generation for creative workflows.
Multi-agent system that searches the web, reads papers, synthesizes findings, and writes structured reports.
Generative AI course location — Netaji Subhash Place (NSP). 2 minutes from NSP Metro Station (Red Line).
NSP Business Hub, Netaji Subhash Place,
New Delhi – 110034
Everything about the Generative AI course in Netaji Subhash Place (NSP), Delhi.
Join the best Generative AI course in NSP. Batch starts July 2026 — only 20 seats per batch. Book your free demo today.
NSP Business Hub, Netaji Subhash Place, New Delhi – 110034
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