COURSE DESCRIPTION
Course last Updated -August 2025 with topic : Claude Code - The Power of AI at terminal level
Eager to learn and catch up with all the AI stuff? - You are at right place.
This AI Testing course is designed to be your ideal companion, teaching how to use AI applications for your daily testing needs.
Firstly, we will start with basic understanding of what AI Applications, Large language models & AI Agents are! And then we deep dive into course content as three learning phases:
Below is the breakup
Module 1. Use of Generative AI for Testing
Module 2. How to Generate Test plan, Test Data, Test cases, UI Automation codes
Module 3. AI Agents to drive Test Automation ~~ Slightly Technical
Module 4. AI powered Testing tools.
What you'll learn
-
Learn how to use Gen AI LLM's effectively to maximize your QA Productivity with smart prompt engineering skills
-
Understand how to Generate & optimize the Test code into framework standards with Gen AI Plugins such as Github copilot etc
-
Get overview of AI Powered Testing tools in current market and their capabilities for revolutionizing Test Automation
-
Learn how AI Agents work and how they can be used to perform Codeless browser Automation with help of LLM's
-
Understand how to work with offline LLM's with full privacy and customize the LLM as per your project requirements
-
Learn generating Test Artifacts in fly such as TestPlan, Testcases, TestData, Bug templates for given Business requirements
-
Learn generating API Automation tests to framework level & SQL Queries with simple prompting to AI
COURSE CURRICULUM
Section 1: Course Introduction - Content overview
Available in
days
days
after you enroll
Section 2: Prompt Engineering - Understand 3 C's - Context, Constraints, Clarity
Available in
days
days
after you enroll
- Lecture 3: Why Prompt Engineering matters? - Mastering it is an Art. (6:04)
- Lecture 4: Adding Constraints to leverage Zero shot prompting for better AI results (9:19)
- Lecture 5: Practice scenarios for crafting prompts better & Few shot prompting technique (6:09)
- Lecture 6: Chain of thought prompting - Let AI detail us on how it is thinking (6:29)
Section 3: Understand Tokens & Generate Test Plan, Test Cases, Test Strategy using AI
Available in
days
days
after you enroll
- Lecture 7: What are tokens? Why it matters when interacting with AI Models (6:59)
- Lecture 8: Understand how Context Window Limit works - Tips to save tokens (6:53)
- Lecture 9: Generating Test Plan for the Project business requirements using AI (13:15)
- Lecture 10: Generating Test Cases for the requirements using AI (10:11)
- Lecture 11: Generating Test Strategy (Shift Left Testing) with the given Test cases using AI (9:11)
- Lecture 12: Generate Test Data combinations for the given tests using AI (10:19)
- Lecture 13: Privacy & Security of AI Applications- How companies are evolving to adapt (5:18)
GitHub Copilot Fundamentals — Ask, Agent, Planning Modes & IDE Installs
Available in
days
days
after you enroll
- Lecture 14: Introduction to GitHub Copilot and it features for AI Integration inside editors (9:10)
- Lecture 15: Demonstration of Ask & Agent modes in Copilot with in VS code with demo examples (10:01)
- Lecture 16: Understanding how Planning mode helps for research and suggest design solutions (7:54)
- Lecture 17: GitHub copilot install on -IntelliJ & Pycharm Editors for Java & Python Projects (5:10)
- Lecture 18: GitHub copilot install steps with overview on -Eclipse Editors for Java project (5:41)
- Lecture 19: GenAI Github copilot plugin for Selenium Java Frameworks within Intellij Editor (30:46)
Section 5: Intro to Model Context Protocol (MCP) Servers & Build Agents with MCP tooling
Available in
days
days
after you enroll
- Lecture 20: What is MCP? How this MCP help an LLM to be super powerful (28:09)
- Lecture 21: Resources to download
- Lecture 22: Build Agent which automates web browser using Playwright/Selenium MCP Servers (14:36)
- Lecture 23: Debugging steps when there are failures in configuring MCP servers
- Practice Role Play 3: Justifying the use of MCP to Your Project Manager
- Lecture 24: Resource
- Lecture 25: Build Agent which can extract data from SQL database by framing complex queries (23:40)
- Lecture 26: Hands-On Practice Resources for Testing Skills
- Lecture 27: Build Agent which can perform API Testing & talk to local File systems for data (18:29)
- Lecture 28: Build Agent which can read/write to excel file for any given scenario (10:40)
- Lecture 29: Setting up Playwright MCP configuration with in VS Code and generate Tests (10:53)
Section 6: Building Agentic AI for Quality Engineering using Claude Code
Available in
days
days
after you enroll
- Lecture 30: Introduction to Agentic AI - What problems we are solving here? -Action Plan (9:51)
- Lecture 31: Introduction to Claude Code Skill System - Problem statement (5:50)
- Lecture 32: Download the code base used in this section
- Lecture 33: Install Claude code & Claude for Chrome and get started with /init file (10:58)
- Lecture 34: Tip - Good to know
- Lecture 35: Understand Knowledge Skills & Agent Skills - When to use with demo example (7:30)
- Lecture 36: Create Skill docs for EventHub Application & Understand how they are designed (13:14)
- Lecture 37: Avoid Context Bloat: Use Smart References for Accurate AI Responses (6:07)
- Lecture 38: The Magic of Agent creating Test Scenarios by reading the Project domain doc (9:49)
- Lecture 39: The Magic of Agent Creating Test Strategy to push tests into different layers (15:45)
- Lecture 40: Create Skills for Playwright best Practices and then build Agent to write Tests (15:01)
- Lecture 41: Demo: Agent Running Tests and Fixing Failed Tests by Referring to Domain Docs (16:50)
- Lecture 42: Tip - Good to know
- Lecture 43: Demo : Goal oriented Agentic Solution for the Test coverage anaylsis with report (11:19)
Section 7: Design GitHub Copilot Custom Agents & Cloud Agents for Automation Repositories
Available in
days
days
after you enroll
Section 8: Build QA Devops Solutions (CI/CD, Docker, GitHub Actions) with AI Agents
Available in
days
days
after you enroll
- Lecture 47: With AI Agents Implement CI/CD using GitHub Actions & push code to Remote GIT (7:02)
- Lecture 48: Demo of CI/CD in Action with simple prompt solution using Claude code AI Agent (11:26)
- Lecture 49: Implement Docker Solution to containerize the Tests in local with AI Agent (15:40)
- Lecture 50: Practical Conversations between Manager & QA Person on building Devops solutions
Section 9: Build AI Agents with n8n Automation workflows - Demo examples
Available in
days
days
after you enroll
- Lecture 51: What is n8n? Overview of Business Process Automation worflows (8:15)
- Lecture 52: How n8n revolutionized with AI Agents encapsulation - Demo overview (7:29)
- Lecture 53: Create n8n AI Agent to read the Google Sheet and identify the bugs in New Status (9:08)
- Lecture 54: Setting up Jira cloud and Create a Project for AI Agent setup (6:22)
- Lecture 55: Plugin Jira tool to AI Agent and create e2e n8n Workflow for business usecase (13:38)
- Lecture 56: Building a Public Chat Interface to Interact with n8n AI Workflow via Webhook (5:09)
Section 10: Generating Automation Code for API Applications using AI
Available in
days
days
after you enroll
- Lecture 57: Using Generative AI for API Testing- parsing Json responses (9:37)
- Lecture 58: Generating POJO classes for complex Json and generate Java methods using AI (11:12)
- Lecture 59: Generating API tests in Cypress & Playwright with the given API contract (10:15)
- Lecture 60: Generating complex SQL Queries for Database tables using AI (9:50)
- Quiz 1: Check your knowledge on MCP, LLM and AI Agents
Section 11: Agentic AI - Introduction to LLM Powered Test Automation Tools
Available in
days
days
after you enroll
- Lecture 61: Gen AI Testing vs LLM Powered Automation testing tools - overview (5:15)
- Lecture 62: Introduction to ContextQA - Upload requirements to generate Testcases (12:27)
- Lecture 63: Links for Handson with ContextQA Platform
- Lecture 64: ContextQA - Turning Manual Test into executable Test Automation steps with demo (8:27)
- Lecture 65: Deep dive into ContextQA Features - Environment variables, Test Suites -Part 1 (8:04)
- Lecture 66: Organizing tests and create Release Test Plan powered by Test execution on Cloud (7:50)
- Lecture 67: Context QA Browser plugin to record Browser Actions & generate executable tests (11:33)
- Lecture 68: TestMu AI Demo - Quality Engineering Platform in the era of AI
Section 12: Privacy first, offline LLM Models to effortlessly handle your Project Domain
Available in
days
days
after you enroll
Section 13: Final words - Interview Questions & Future of AI in QA Space
Available in
days
days
after you enroll
- Lecture 70: Interview Questions to crack your next Job - Recap the topics (28:53)
- Lecture 71: Introduction to GPT4All - and how it works offline to generate results (8:27)
- Lecture 72: How AI can be your best buddy for coding practice and implementation (8:26)
- Lecture 73: Future proof your QA-AI Skills - What next? (3:53)
- Lecture 74: Thankyou Note with future updates Plan
- Lecture 75: Bonus Lecture
This course includes
- 10.5 hours on-demand video
- Assignments
- 6 articles
- 4 downloadable resources
- Access on mobile and TV
- Certificate of completion
Pioneering
Embark on the Cutting-Edge of Automation with Generative AI in Software Testing
Comprehensive
Mastering the Full Spectrum of Generative AI Applications in Quality Assurance
Innovative
Transforming Software Quality with Next-Generation AI Testing Techniques
Testimonials
Excellent course and Rahul Shetty sir explanation about the course and practically demo the course are brilliant. Thanks.
-- Naveen K.
I loved this course. Clear explanations and practical examples made learning Agentic AI very easy and engaging. Totally worth the 5/5 rating.
-- Yash K.
I have learned about how to use with Agentic AI, Claude and GPT along with MCP server configuration ,insightful course.
-- Preethi B.
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.
Check your inbox to confirm your subscription