Generative AI is transforming how intelligent applications are built, and Large Language Models (LLMs) are at the center of this evolution. This advanced course is designed for AI professionals who want to move beyond using AI tools and begin building, fine-tuning, and deploying production-ready Generative AI applications.

Through hands-on projects, you'll explore modern AI frameworks, LLM architectures, Retrieval-Augmented Generation (RAG), fine-tuning techniques, and Agentic AI systems. By the end of the course, you'll have the practical skills to develop intelligent applications using industry-standard tools and deploy real-world AI solutions with confidence.

What You'll Learn

This course provides a practical, project-based approach to modern Generative AI development. Throughout the course, you'll explore:

• Fundamentals of Large Language Models (LLMs)
• Generative AI architectures and workflows
• Working with frontier and open-source AI models
• Building applications using Hugging Face, LangChain, and Gradio
• Retrieval-Augmented Generation (RAG)
• Fine-tuning LLMs using modern techniques such as QLoRA
• Designing and deploying Agentic AI systems
• Building production-ready AI applications
• Deploying AI solutions with user-friendly interfaces

Learning Outcomes

By the end of this course, learners will be able to:

• Understand the architecture and capabilities of modern Large Language Models.
• Build end-to-end Generative AI applications using industry-standard frameworks.
• Implement Retrieval-Augmented Generation (RAG) for knowledge-based AI systems.
• Fine-tune open-source language models for domain-specific applications.
• Design and develop intelligent AI agents capable of performing complex tasks.
• Deploy scalable AI applications with production-ready interfaces.
• Build a portfolio of real-world Generative AI projects using modern development practices.

Tools & Skills Covered

• Large Language Models (LLMs) - Understand how modern language models are trained, deployed, and applied across industries.
• Generative AI Frameworks - Build AI applications using Hugging Face, LangChain, and Gradio.
• Retrieval-Augmented Generation (RAG) - Enhance LLM performance by integrating external knowledge sources.
• LLM Fine-Tuning - Learn modern techniques such as QLoRA to customize models for specialized tasks.
• Agentic AI Systems - Design autonomous AI agents capable of reasoning, planning, and executing multi-step tasks.
• AI Application Deployment - Deploy production-ready AI solutions with intuitive user interfaces.

What Makes This Course Special?

• Designed for AI Professionals looking to master modern Generative AI development.
• Project-Based Learning focused on building practical, portfolio-ready AI applications.
• Industry-Standard Tools including Hugging Face, LangChain, Gradio, and leading LLM ecosystems.
• Advanced AI Techniques covering RAG, fine-tuning, model optimization, and Agentic AI.
• Real-World Development Experience through applications inspired by modern enterprise AI use cases.
• Future-Ready Curriculum that reflects the latest advancements in Generative AI and LLM technologies.

Prerequisites

To get the most out of this course, learners should have:

• A working knowledge of Python programming.
• A Windows, macOS, or Linux computer with an internet connection.
• Basic familiarity with programming concepts and AI fundamentals.
• An optional budget for API usage when working with frontier models (open-source alternatives are also supported).

By completing this course, you'll gain the technical expertise to build, fine-tune, and deploy advanced Generative AI applications using modern LLM frameworks and Agentic AI systems. Whether you're developing enterprise solutions or expanding your AI portfolio, this course will prepare you for the next generation of intelligent application development.