COURSE DESCRIPTION
Welcome to the future of AI Automation – Agentic AI with the AutoGen Framework.
This course is your ultimate guide to building intelligent, autonomous AI agents that collaborate, self-correct, and execute complex tasks without constant human intervention.
Even if you're new to this space, we start from the absolute basics—no prior knowledge of agent frameworks is required.
You’ll start by mastering the core foundations – Large Language Models (LLMs), AI Agents, Multi-Agents, and the Model Context Protocol (MCP), which serves as the backbone for agent-to-tool communication.
Next, you’ll learn how to engineer contexts and craft prompts that unlock the true potential of your AI agents.
By the end, you’ll have the skills to create production-ready agentic systems using the Agent Factory Pattern, empowering you to design reusable, scalable, and highly efficient AI workflows.
If you’re ready to level up from AI users to AI builders, this course will give you the tools and mindset to lead the next wave of AI innovation.
What you'll learn
- Get a detailed understanding of LLMs, AI Agents, MCP, Multi-Agent Systems, and Agentic AI
- Build Multi Agentic workflows using Microsoft AutoGen Framework
- Develop Specialized Agents such as Jira Agent for Bug analysis, Playwright Agent for browser Automation, API Agent for testing, DB Agent for data analysis
- Build intelligent, autonomous AI agents that collaborate, self-correct, and execute complex tasks without constant human intervention
- Understand the power of Context Engineering to enable AI agents to work effectively toward defined goals
- Build an Agent Factory design pattern to create reusable specialized agents for multi-purpose use
- Get in-depth knowledge of MCPs and how their configurations are defined for real-world applications
Who is this course for
- QA Engineers.
- AI Engineers
- Developers
- Software Engineers
-
Business Analyst /Managers
COURSE CURRICULUM
- Lecture 4: Important Note
- Lecture 5: What is MCP? How this MCP help an LLM to be super powerful (28:09)
- Lecture 6: Resources to download
- Lecutre 7: Build Agent which automates web browser using Playwright/Selenium MCP Servers (14:36)
- Lecture 8: Debugging steps when there are failures in configuring MCP servers
- Lecture 9: Build Agent which can extract data from SQL database by framing complex queries (23:40)
- Lecture 10: Build Agent which can perform API Testing & talk to local File systems for data (18:29)
- Lecture 11: Build Agent which can read/write to excel file for any given scenario (12:49)
- Lecture 12: Disadvantages of having Single Agent - and how Multi Agent fixes the problem (5:48)
- Lecture 13: What is Agentic AI? Importance of Multi Agent work flows (8:36)
- Lecture 14: Setting up Python and IDE to get started in Windows Machine (6:16)
- Lecture 15: Setting up Python and IDE to get started in MAC Machine (6:42)
- Lecture 16: Setup Python virtual enviroment & install AutoGen packages into Python Env (9:54)
- Lecture 17: How to kickstart running any python code and its function call (4:51)
- Lecture 18: Introduction to AssistantAgent and its implementation with an example (12:53)
- Lecture 19: How to make AssitantAgent answer the multimodal inputs such as images, files (14:39)
- Lecture 20: What is RoundRobinGroupChat? How to coordinate between agents in a team (11:46)
- Lecture 21: Full course code download
- Lecture 22: What is Termination Condition and why do we need it? -MessageMax termination (8:13)
- Lecture 23: How to get human in loop - Intro to UserProxyAgent class in AutoGen (17:18)
- Lecture 24: State Saving Mechanism - How to switch between agents preserving state (14:06)
- Lecture 25: SelectorGroupChat - How to dynamically choose which agent to act in teams (16:06)
- Lecture 29: Understand the Goals of the Multi Agent workflow with a plan of execution (6:30)
- Lecture 30: Setup Cloud Jira account for Agenti AI project execution (6:22)
- Lecture 31: High level overview on how to create bugs and retrieve with in Jira project (7:17)
- Lecture 32: Understand how to add Jira Environment variables into Assistant Agent - demo (12:31)
- Lecture 33: Create Jira Agent with Integrating Jira mcpworkbench into Assistant Agent (10:47)
- Lecture 34: Create Browser Automation Agent with Integrating Playwright mcpworkbench (5:41)
- Lecture 35: Important : Setting up context to Jira & Browser Agents for achieving the goal (15:49)
- Lecture 36: Context - System messages of Jira
- Lecture 37: Context - System messages of Browser Agent
- Lecture 38: Complete end to end workflow to build Agentic AI solution with RoundRobin Teams (9:00)
- Lecture 39: Run the Multi Agentic workflow & analyze the agents output behaviour in detail (11:50)
- Lecture 40: Database-API-Excel -Understand the Goals of the Multi Agents and its workflow (6:32)
- Lecture 41: What is AgentFactory? How to isolate and create Agents within factory (12:18)
- Lecture 42: Part 1 - Build mcp Config file & connect Factory ,Config file to main test flow (7:28)
- Lecture 43: Part 2 - Build mcp Config file & connect Factory ,Config file to main test flow (9:07)
- Lecture 44: Complete end to end workflow to build Agentic AI solution with AutoGen concepts (5:56)
- Lecture 47: Recap of Agenti AI - Multi Agent workflow concepts learned in the course (4:48)
- Lecture 48: Code download
- Lecture 49: Resume inputs what you can add with the skills gained from this course
- Lecture 50: Part 2-Provide System messages to Database, API, Excel Agents in logical manner (14:28)
- Lecture 51: Python hello world Program with Basics (8:35)
- Lecture 52: Datatypes in python and how to get the Type at run time (5:17)
- Lecture 53: List Datatype and its operations to manipulate' (12:47)
- Lecture 54: Tuple and Dictionary Data types in Python with examples (8:28)
- Lecture 55: If else condition in python with working examples (3:10)
- Lecture 56: How to Create Dictionaries at run time and add data into it (7:55)
- Lecture 57: How loops work in Python and importance of code idendation (8:58)
- Lecture 58: Programming examples using for loop - 1 (4:17)
- Lecture 59: Programming examples using While loop - 2 (10:28)
- Lecture 60: What are functions? How to use them in Python (10:46)
- Lecture 61: OOPS Principles : Classes and objects in Python (7:38)
- Lecture 62: What is Constructor and its role in Object oriented programming (13:38)
- Lecture 63: Inheritance concepts with examples in Python (12:12)
- Lecture 64: Strings and its functions in python (9:53)
- Lecture 65: Bonus Lecture
This course includes
- 10 hours on-demand video
- Access to 9 articles
- Access to 6 downloadable resources
- Access on mobile and TV
- Full lifetime access
- Certificate of completion
Pioneering
Leading the Future of Automation with Agentic AI and Multi-Agent Workflow Orchestration
Practical
Hands-On Agentic AI: Build, Coordinate, and Deploy Multi-Agent Automations
Innovative
Reimagining Business Processes through Agentic AI and Collaborative Multi-Agent Systems
Testimonials
“Thank you @Rahul Shetty for simplifying such a complex AI topic. I now feel ready to step into the world of the Autogen framework in testing. I truly appreciate you publishing this course—I’m really glad I took it.”
-- Sagar K.
A big thank you to Rahul Shetty for designing such a powerful and practical course. Your clarity in explaining agentic systems, LLM orchestration, and automation frameworks helped me dive deep into one of the most exciting areas of AI!
-- Anil S.
Was eagerly waiting for this course. Rahul has tremendous capability of explaining things in simple terms. Had seen many videos on MCP but initially was not able to grasp full concept, one YT video on MCP by Rahul cleared various doubts I had. Had some idea regarding Autogen, this course helped on understanding how various tools can be integrated with Autogen and real life use cases that can be explored. Thanks again for crafting another well thought out course.
-- Debabrata C.
About Instructor
"Teaching is my Passion. And it's my Profession. The only Business I know is Spreading Knowledge."
I'm Rahul Shetty (aka- Venkatesh), a QA instructor with a 15-year track record. Over 1 Million QA professionals from 195 countries have taken my courses on Selenium, Playwright, AI Testing, Software Testing (Jira), API Testing, Cypress, Postman, Appium, JMeter, and more..."
I lead top QA initiatives both online and offline — through Rahul Shetty Academy, one of the leading EdTech platforms for QA training; QASummit, a premier offline conference brand; and RS TekSolutions, my software consulting firm. Together, these ventures have helped hundreds of thousands of students master testing and automation, transforming their careers as Automation Engineers
