Generative AI from Basic to Advance - Vibe Engineering (Coding) Crash Course | Build AI Customer Support Agent with AWS Deployment

Master Generative AI: From Basics to Breakthroughs in AI Models and RAG Systems

5.0 (2)

26 learners

What you'll learn

Understand the evolution of generative AI from classical to modern techniques
Apply RAG and LangChain for building scalable AI applications
Implement end-to-end pipelines using LlamaIndex and LLM fine-tuning methods
Deploy AI models with CI/CD pipelines and container orchestration tools

This course includes

124.5 hours of video
Certificate of completion
Access on mobile and TV

Summary

Keywords

vibe engineering vibe engineering crash course vibe coding vibe coding tutorial ai agents build ai agents ai agents tutorial ai agents project ai agents end to end ai agents aws deployment aws deployment tutorial deploy ai agents on aws

Full Transcript

In this **Vibe Engineering Crash Course**, I show you how modern AI-powered software is actually built from **LLM fundamentals** to **AI coding agents** to **deploying a real project on AWS**. ## Chapters 0:00 Introduction and Welcome 1:06 Course Roadmap Overview 6:01 Why Learn Vibe Engineering Right Now? 11:05 LLMs Explained: The Intelligence Engine 13:24 The ReAct Loop: How AI Agents Think and Act 17:03 Coding AI Agents vs Plain LLMs 21:44 Prompting Effectively: The Genie Analogy 29:50 Vibe Coding vs Vibe Engineering: Key Differences 32:11 Context Window: The LLM's RAM 38:49 Prompt vs Context: A Critical Distinction 41:55 Agent Skills and Smart Context Management 46:53 Coding Agent Types: CLI, IDE, and Cloud 54:17 GitHub Copilot: Setup, Modes, and Features Tour 1:14:56 Cursor IDE: Features, Settings, and Context Tools 1:34:03 Antigravity IDE by Google: Overview and Tour 1:42:07 Project: Building an AI Customer Support Agent 1:49:48 Planning Phase: Architecture and Mermaid Diagram 2:04:22 Live Build: Agent Generates the Full App 2:10:01 Adding Production Logging and UV Package Manager 2:23:36 Running and Testing the App Locally 2:30:32 Deploying to AWS EC2 Using CLI 2:50:14 Live Demo on AWS + Course Wrap-Up This is not surface-level theory. This is a full practical walkthrough for developers and builders who want to understand how to move from **vibe coding** to **vibe engineering**. Inside this course, you’ll learn: - how **LLMs** work in real product-building workflows - what the **ReAct loop** actually means - the difference between **prompt vs context** - why **context windows** matter so much - what **AI coding agents** are - how **agent skills** help control context and workflows - the types of coding agents in the market: **CLI, IDE, and Cloud** - overview of **GitHub Copilot, Cursor, and Google Antigravity** - how to build a **real AI customer support agent** - how to design the architecture and Mermaid diagram - how to generate the app, run it locally, improve production logging, and deploy it to **AWS EC2 using AWS CLI** **Real Project Covered** In the second half of the course, we build an **end-to-end AI customer support agent** for a practical business use case. The project focuses on a **compliance report generator** that works by analyzing transcript data generated from audio, and then turning that into a structured support/compliance workflow. So this course does not just teach concepts. It shows you how to actually **ship something real**. **Who this is for** This course is for: - developers - AI builders - students exploring coding agents - anyone curious about **Cursor, Copilot, Antigravity, context engineering, and agent-based development** If you want to understand where AI-assisted software development is going, this course will help you build the right mental model. **Mentor / Creator Links** - **Yash Patil LinkedIn:** [Yash Patil](https://www.linkedin.com/in/yash-patil-ai/) - **Sunny Savita LinkedIn:** [Sunny Savita](https://www.linkedin.com/in/sunny-savita/) - **Yash Patil YouTube:** [@yashpatil953](https://www.youtube.com/@yashpatil953) - **Yash Patil GitHub:** [yashprogrammer](https://github.com/yashprogrammer) - **Sunny Savita GitHub:** [sunnysavita10](https://github.com/sunnysavita10) #AI #GenerativeAI #GenAI #LLMOPS #LangChain #LangGraph #AIagents #AgenticAI #StructuredOutput #AIautomation #RAG #AdvancedRAG #FAISS #LlamaIndex #LCEL #Python #Chatbot #OpenAI #GPT #Gemini #Google #FastAPI #AWS #CICD #AIProjects Don't miss out; learn with me! P.S. Don't forget to like and subscribe for more AI content! End-to-End-Langgraph-Project: https://github.com/sunnysavita10/doctor-appoitment-multiagent Multimodel RAG Playlis: https://www.youtube.com/watch?v=7CXJWnHI05w&list=PLQxDHpeGU14D6dm0rmAXhdLeLYlX2zk7p&pp=gAQBiAQB RAG detailed Playlist: https://www.youtube.com/watch?v=wTVTkOb3SZc&list=PLQxDHpeGU14Blorx3Ps1eZJ4XvKET1_vx&pp=gAQBiAQB GenAI Foundation Playlist: https://www.youtube.com/watch?v=ajWheP8ZD70&list=PLQxDHpeGU14D7NiPgqxC9qhKkx4jMQcDk&pp=gAQBiAQB Connect with me on Social Media- LinkedIn : https://www.linkedin.com/in/sunny-savita/ One to One Call: https://topmate.io/sunny_savita10 GitHub : https://github.com/sunnysavita10 Telegram : https://t.me/aimldlds