Generative AI Masters: Building LLM Applications

Become a Generative AI Builder

Generative AI is transforming every industry — from finance and healthcare to SaaS and education. In this hands-on course, you will go beyond theory and learn how to build, deploy, and scale real-world applications powered by Large Language Models (LLMs). If you want to move from simply using ChatGPT to engineering production-ready AI systems, this course is for you.

Master Large Language Models from the Inside Out

We begin with a practical understanding of how transformer-based LLMs work, including tokens, embeddings, context windows, and inference mechanics. You will gain the technical clarity needed to design systems that are reliable, efficient, and scalable.

Then, we move into advanced prompt engineering techniques, including:

• Zero-shot and few-shot prompting
• Chain-of-thought reasoning
• System prompts and structured outputs
• Prompt evaluation and optimization

Build Real LLM Applications

This course is deeply practical. You will build applications using the OpenAI API and open-source tooling, integrating streaming responses, function calling, and external tools. By the end of the program, you will have developed multiple portfolio-ready AI systems.

We focus heavily on Retrieval-Augmented Generation (RAG), one of the most in-demand skills in Generative AI engineering. You will:

• Create embeddings and semantic search pipelines
• Use vector databases for document retrieval
• Design high-performance RAG architectures
• Evaluate and improve answer quality

Design and Deploy AI Agents

Learn how to build intelligent AI agents capable of using tools, calling APIs, and maintaining memory. You’ll implement structured tool usage, manage state, and apply safety guardrails to ensure responsible AI behavior.

Production-Ready Deployment

Building a demo is easy. Deploying a scalable LLM system is not. That’s why we cover:

• FastAPI-based backend deployment
• Docker containerization
• Cloud deployment strategies
• Latency and cost optimization
• Monitoring and observability

Who This Course Is For

This course is ideal for software engineers, ML practitioners, data scientists, and technical founders who want to master Generative AI engineering. If you are serious about building LLM-powered products, this program gives you the tools and architecture patterns used by top AI teams.

Ready to level up your AI skills? Register free or browse all courses to explore more elite AI training programs from Edu AI.

By the end of this course, you won’t just understand Generative AI — you’ll be able to design, build, and deploy sophisticated LLM applications with confidence.

What You Will Learn

• Understand the architecture and capabilities of large language models (LLMs)
• Design and optimize advanced prompts for reliable outputs
• Build LLM-powered applications using OpenAI and open-source models
• Implement Retrieval-Augmented Generation (RAG) pipelines
• Develop autonomous AI agents with tool usage
• Integrate vector databases for semantic search
• Deploy scalable LLM apps with APIs and cloud services
• Apply guardrails, evaluation, and safety best practices
• Optimize performance, cost, and latency in production
• Create portfolio-ready generative AI projects

Requirements

• Basic Python programming knowledge
• Familiarity with APIs and REST concepts
• Understanding of fundamental machine learning concepts
• A laptop capable of running Python and installing packages