GenAI & AI Agents for Java Spring Boot Devs | Copilot,Claude (Udemy.com)
Claude Code, GitHub Copilot, MCP, n8n, Google Antigravity, Prompt Engineering, AI Agents that Automate Real Dev Workflow
Created by: Faisal Memon (EmbarkX)
Last updated August 2026
What you will learn
- AGENTIC AI FUNDAMENTALS - Understand how LLMs, context windows, tokens and hallucinations work so you can build agents that are reliable in production
- PROMPT ENGINEERING - Write production-grade system prompts, slash commands and memory files that keep your agents reliable across long agentic tasks
- CLAUDE CODE - Master terminal-native agentic coding with filesystem ownership, slash commands, memory files, subagents and MCP server integration
- GITHUB COPILOT - Use Agent Mode, Next Edit Suggestions, Copilot CLI, AGENTS md and Copilot Cloud Agent to automate real workflows inside GitHub
- MCP SERVERS - Connect GitHub, and Filesystem MCP servers to give your agents real tools and secure them against prompt injection attacks
- N8N & EVENT-DRIVEN ORCHESTRATION - Trigger agent workflows from GitHub and Slack using n8n and chain them with Claude Code for full automation
How it compares
Against the other 518 rated Udemy courses in Software Development on CourseDuck:
- Rating4.5 out of 5higher than 41% of them
- Reviews130#409 of 519 by number of reviews
- Length10.4 hourslonger than 69% of them
- Last updatedAugust 2026more recently than 88% of them
Course Description
Most AI courses teach you to use AI tools. This one teaches you to build AI agents that do engineering work autonomously — running in your CI pipelines, reacting to events, and fixing problems without waiting for you.
This is a hands-on course for freshers-mid-to-senior software engineers ready to move from AI user to AI agent builder.
You won't be building toy demos. Every agent in this course solves a real problem: automated PR reviews, slow query detection, with human approval gates, and more. Each build introduces a distinct architectural pattern you can adapt to your own stack.
What you'll learn
How LLMs actually work: context windows, hallucinations, token limits, and why it matters when you're building agents, not just chatting
Prompt engineering that holds up in production agent contexts
Claude Code: terminal-native agentic coding with filesystem ownership and MCP integration
GitHub Copilot: IDE-native and GitHub Actions agentic workflows
OpenAI Codex: async task delegation with PR-based output
Google Antigravity / Google Gemini: multimodal terminal input for Google ecosystem teams
MCP servers: extending your agents with custom tools and external integrations
n8n: event-driven orchestration that connects your agents to the rest of your workflow
JetBrains AI: Run all AI tools inside IntelliJ IDEA
Who this is for
Software engineers or Freshers who want to build and deploy real AI agents
Java and Spring Boot developers integrating AI into existing backend systems
DevOps and cloud engineers looking to automate repetitive operational work
Any developer tired of demos and ready to run agents in actual CI/CD pipelines
Requirements
Comfortable with at least one backend language (Java or Spring Boot experience is a plus)
No prior AI or machine learning experience needed
Instructor Details
- 4.5 Rating
130 Reviews
Faisal Memon (EmbarkX)
I'm the founder of EmbarkX, a global developer education platform trusted by over 300,000 learners worldwide. My mission is to bridge the gap between what universities teach and what the industry actually demands — building engineers who are production-ready, not just tutorial-ready.
With a background spanning multiple ventures and recognition as a Google Accelerator alumnus, I've been at the forefront of reimagining how software engineers learn, grow, and build careers in a rapidly evolving tech landscape.
I am here on Udemy to share my knowledge with seekers and help them grow personally and professionally.
Glad to meet you :)
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Reviews
By Aadithya on 9/12/2026
I find this course interesting. I just started and want to know more about AI and how to include it to make me more productive.
By Ranjeet Patel on 8/11/2026
New things are great to know from you as learning. But I would request you please include current tools that used over enterprise application. Just as pop-snippet tools/description while talking to same.
By Rahul Gupta on 8/2/2026
Yes, its a perfect learning program for new people in Agentic AI
By Shelendra Rathore on 7/28/2026
One of the best courses I've taken on AI Agents for software engineers. I learned a lot from this course—from understanding how LLMs actually work (context windows, hallucinations, token limits, and prompt engineering) to building real-world AI agents for engineering workflows. What I liked most is that the course focuses on practical, production-ready use cases instead of simple demos. The sections on Claude Code, GitHub Copilot, MCP servers, n8n, and AI-powered CI/CD automation were especially valuable. The explanations are clear, hands-on, and easy to follow. I now have a much better understanding of agentic AI architecture and how to apply it in real Java/Spring Boot projects. Thanks to the instructor for creating such a practical and well-structured course. I highly recommend it to any Java/Spring Boot developer or software engineer who wants to build real AI agents and stay ahead in AI engineering.
By Anitha Pasupala on 7/26/2026
Very Good Explanation
By Prashanth on 6/27/2026
This is a well-structured course that follows a clear step-by-step approach. The instructor first builds a solid foundation before gradually introducing more advanced concepts, making the learning process easy to follow and understand. The logical progression and organization of the content made it an enjoyable and effective learning experience.
By Prashant Jha on 9/13/2026
By Mohan raj G on 9/8/2026
By Rajesh Aharwal on 7/17/2026
By Tejab Titare on 6/26/2026
Quality Score
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Overall Score : 90 / 100









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