Advanced LLM Engineering, RAG & Agentic AI
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Course Description
Master the technologies powering today’s most advanced AI applications. This comprehensive program takes you from understanding modern Large Language Models (LLMs) to building production-ready AI agents, Retrieval-Augmented Generation (RAG) systems, and enterprise-grade AI applications.
You’ll gain practical experience with GPT, LangChain, LangGraph, Ollama, MCP, Fine-Tuning, and Production Deployment by building real-world projects every week. By the end of the course, you’ll have a professional portfolio featuring AI assistants, autonomous agents, RAG systems, and a complete production-ready LLM application.
What You’ll Learn
- Master Modern Large Language Models and Transformer architectures.
- Write effective prompts using advanced prompting techniques.
- Build powerful Retrieval-Augmented Generation (RAG) applications.
- Develop enterprise-grade AI knowledge assistants.
- Create intelligent workflows using LangChain.
- Design autonomous AI agents with LangGraph.
- Evaluate AI systems using modern LLM evaluation frameworks.
- Run open-source LLMs locally with Ollama.
- Fine-tune LLMs using LoRA, QLoRA, and PEFT.
- Build AI Agents using MCP and external tools.
- Deploy scalable AI APIs using FastAPI and Docker.
- Build a complete production-ready Agentic AI application.
- 12 Sections
- 24 Lessons
- 10 Weeks
Expand all sectionsCollapse all sections
- Section 1 – Foundations of LLM Engineering2
- Week 2 • Prompt EngineeringLearnPress integrates with popular tools to enable live online courses.2
- Week 3 • RAG FundamentalsLearnPress LMS Plugin is free to use and offers a robust set of features to get you started.2
- Week 4 • Advanced RAGThis section walks you through all the essential LearnPress settings to get you started.2
- Section 2 – Agentic AI DevelopmentWeek 5 • LangChain2
- Week 6 • LangGraph & Agentic AI2
- Week 7 • LLM Evaluation2
- Week 8 • Ollama & Local LLMs2
- Section 3 – Production AI SystemsWeek 9 • Fine-Tuning LLMs2
- Week 10 • AI Agents & MCP2
- Week 11 • Production Systems2
- Week 12 • Capstone Project2
This course teaches you how to build modern AI applications using Large Language Models, RAG, LangChain, LangGraph, MCP, and Agentic AI from beginner-friendly fundamentals to production deployment.
Yes. Basic Python knowledge is recommended, and every concept is taught step by step with practical implementation.
Python is used throughout the course along with modern AI frameworks and developer tools.
Yes. Every module includes a practical project, and you'll complete a production-ready capstone AI application by the end.
You'll work with GPT, LangChain, LangGraph, Ollama, FastAPI, Docker, Redis, Vector Databases, LangSmith, Ragas, TruLens, and many other industry-standard tools.
No. Many exercises can be completed using Google Colab or cloud platforms. You'll also learn how to run local LLMs efficiently.
Yes. A course completion certificate will be awarded after successfully completing the program and final capstone project.
This course prepares you for roles such as AI Engineer, LLM Engineer, Generative AI Engineer, ML Engineer, RAG Developer, AI Application Developer, and Agentic AI Engineer.
mentorzoadmin
11 Students12 Courses
Features
- Industry-Focused Curriculum
- Hands-on Weekly Projects
- Production Deployment Training
- Modern AI Frameworks
- Local & Cloud LLM Development
- Enterprise RAG Systems
- Agentic AI Development
- Portfolio-Ready Capstone
Target Audiences
- AI & Machine Learning Engineers
- Software Developers
- Python Developers
- Data Scientists
- Backend Engineers
- AI Product Builders
- Students interested in Generative AI
- Professionals transitioning into AI
Requirements
- Basic Python Programming
- Familiarity with APIs
- Basic Machine Learning Knowledge
- Computer with Internet Connection
- Passion for Building AI Applications
Price
₹7,000.00
Level Intermediate
51 students
Duration 10 weeks
24 Lessons
Language English
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