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Basics of Agentic AI & Microsoft Agent Framework (MAF) Introduction
7 Lessons -
Creating AI Agents | Implementing Memory in Agents
10 Lessons-
StartDownload Code for Agentic AI - MAF Basics Section
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StartCreate Your First Agent
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StartCreate Agent Which Can Handle Images
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StartHow to Stream Output from Agent
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StartAgent Types and Architecture
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StartImplementing Memory in Agent
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StartSharing Memory Across Multi Agents in Same Session
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StartShare History Across Different Sessions of Agents
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StartSave Agent Chat History to JSON File
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StartAI Agent vs LLM's
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Concurrent, Handoff, Group Chat and Magnetic Orchestrations
6 Lessons -
Project 1 - Bug/Defect Triage Agentic AI Solution
8 Lessons-
StartDownload Code Files for Project 1
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StartBug Triage Solution Agentic AI
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StartGroup Chat Orchestration Demonstration
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StartAdding System Messages to AI Agents
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StartAgent Factory Pattern & Framework Development
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StartAgentic AI Solution - Framework Development Part - 1
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StartAgentic AI Solution - Framework Development Part - 2
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StartAgentic AI Solution - Framework Development Part - 3
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Project 2 - Test Analysis to Automation Script Creation Agentic AI Solution
16 Lessons-
StartDownload Code for Project 2
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StartAgentic AI Solution for Creating Manual Tests and Automation Scripts
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StartBuild Project Structure in Pycharm IDE
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StartUnderstand About AI Agents Needed in this Solution
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StartAI Agent 1 - Create Jira Analyst Agent
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StartConfigure Atlassian MCP Server in AI Agent - Part 1
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StartConfigure Atlassian MCP Server in AI Agent - Part 2
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StartUnderstand in Detail How to Setup Atlassian MCP Server
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StartCreate Jira Story Analyst Agent, Main.py and Sequential Workflow
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StartAdd User Story Analyst Agent and Run the Workflow
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StartCreate Test Case and Playwright Script AI Agents
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StartUpdate SUT in User Story and Create Updated Playwright Script
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StartImplement File System MCP to Save Playwright Test Scripts Locally
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StartInstalling Playwright and Running Tests Create by Agentic AI Solution
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StartUpdating Instructions for Playwright Script Generation
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StartImplementing Human-in-the-loop (HITL) in this Agentic AI Solution
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Python for Testers
47 Lessons-
StartDownload Full Code Files for "Python for Testers" course
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StartIntroduction
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StartIntroduction to Python Tutorial
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StartVariables in Python
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StartVariable Rules in Python
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StartOperators in Python
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StartArithmetic Operators in Python
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StartPython Operator Precedence
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StartBoolean Data Type in Python
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StartWhat are Strings in Python
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StartString Functions in Python
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StartString Slicing in Python
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StartHow to Format Strings in Python
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StartLists in Python
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StartList Methods in Python
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StartSets in Python
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StartSet Methods in Python
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StartTuples in Python
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StartTuple Methods in Python
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StartDictionaries in Python
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StartDictionary Methods in Python
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StartHow to Use if-else in Python
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StartWhile Loop in Python
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StartBreak and Continue in Python
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StartFor Loop in Python
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StartZip Function in Python
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StartRange Function in Python
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StartFunctions in Python
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StartReturn Statement in Python
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StartKeyword and Positional Arguments in Python
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StartVariable Scope in Python
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StartBuild in Functions in Python
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StartDatetime Module in Python
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StartClasses and Objects in Python
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StartCreating Objects and Methods in Python
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StartClass Variables vs Instance Variables in Python
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StartInheritance in Python
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StartMultiple Inheritance in Python
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StartMultilevel Inheritance in Python
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StartModules in Python
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StartException Handling in Python
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StartHow to Write File in Python
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StartHow to Read File in Python
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StartWith Keyword in Python
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StartHow to Write Data to Excel in Python Openpyxl
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StartHow to Read Excel File in Python Openpyxl
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StartHow to Generate Test Data Using Python
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Agentic AI for QA & SDET: Build Autonomous Test Automation
Master Multi-Agent Autonomous AI Workflows for Intelligent QA / Test Automation with Microsoft Agent Framework
Course Summary
I've been doing QA automation for over 20 years. I started at IBM, moved to many organizations like Infosys, ANZ, NAB, Capgemini, and I watched the same thing happen over and over, teams spend weeks writing test cases by hand, running them manually, triaging bugs in spreadsheets. It's tedious. It doesn't scale.
With AI, it doesn't have to be that way.
This course teaches you how to build AI systems that do that work for you. Real systems. Production-ready systems using the Microsoft Agent Framework that you can deploy and use.
☑️ What You'll Build
Two hands-on projects:
Project 1: A Bug/Defect Triage Agentic AI Solution: Build an AI system that reads your Jira tickets, understands what the bug is, figures out how serious it is, assigns it. Learns from the decisions you make and gets better.
Project 2: Test Analysis to Automation Script Creation Agentic AI Pipeline: User story comes in → agent reads it → generates edge cases → writes Playwright tests. The whole flow. You'll learn how to get multiple AI agents working together instead of against each other.
☑️ Why This Actually Works
The hard part about agentic AI isn't the AI part. It's getting multiple agents to coordinate. I spent months debugging race conditions in the Microsoft Agent Framework, figuring out why GroupChat was failing, solving orchestration problems. That's what this course teaches, the real stuff that makes it work.
You learn the foundations fast (what are LLMs, how do agents work). Then you build. Jira integration, Playwright, all woven together with Python.
You also see where things go wrong and how to fix them. That's the difference between a tutorial that leaves you hanging and one that actually prepares you.
☑️ What You'll Learn
✅ How AI agents actually work (not theory, practice)
✅ Microsoft Agent Framework inside and out
✅ Sequential and GroupChat orchestration patterns
✅ Building human-in-the-loop workflows
✅ Connecting to Jira and pulling real data
✅ Generating test cases with AI that make sense
✅ Automating Playwright from agent outputs
☑️ How the Course Flows
✅ Beginning: Foundations. AI agents, LLMs, Microsoft Agent Framework basics. Not too deep, just enough to know what you're doing.
✅ Middle: You build the two projects. Bug triage first (simpler, good mental model). Then the full test automation pipeline.
✅ Advanced: Multi-agent patterns, dealing with GroupChat complexity and other orchestration patterns.
Course Curriculum
