Next-Gen AI Automation Testing with Playwright & TypeScript – Live Training
(AI Testing Fundamentals | Playwright with TypeScript | Prompt Engineering | LLM Validation | API & UI Testing | MCP Integration | CI/CD with GitHub Actions | Real-Time AI Automation Projects)
Step into the future of software testing with our advanced AI-driven automation testing program, designed for professionals and aspiring testers who want to master modern AI testing practices using Playwright and TypeScript.
This course provides complete hands-on training in AI testing foundations, Large Language Model (LLM) validation, prompt engineering, AI response verification, automation framework design, API and UI automation, JSON schema validation, AI scoring systems, CI/CD integration, and real-time project implementation.
Learners will gain practical expertise in building robust automation frameworks for AI-powered applications, validating intelligent system responses for accuracy, relevance, consistency, safety, and performance, while implementing advanced testing strategies used in real-world AI products.
The program includes real-time implementation of AI chatbot testing and AI resume analyzer automation projects, helping students develop practical experience in handling AI workflows, prompt validation, response scoring, structured output verification, file automation, API testing, reporting, and intelligent test execution.
By the end of this training, learners will have strong expertise in AI-powered test automation development, complete real-time projects for professional portfolios, and the confidence to succeed in AI QA Engineer, SDET, and advanced automation testing roles across modern technology-driven organizations.
Sample Videos:
NextGen AI AI Automation Testing with Playwright & TypeScript – Live Training – Demo Recording
NextGen AI AI Automation Testing with Playwright & TypeScript – Live Training – Day 1 Recording
Prerequisite:
- Basic knowledge of Playwright + JavaScript/TypeScript
Live Sessions Price:
For LIVE sessions – Offer price after discount is 300 USD 259 109 USD Or USD13000 INR12900 INR 8900 Rupees
OR
Free Day 3 On:
Indian Timings: 28th May @ 9 PM – 10 PM (IST)/
U.S Timings: 28th May @ 11:30 AM – 12:30 PM (EST)/
U.K Timings: 28th May @ 4:30 PM – 5:30 PM (BST)
Class Schedule:
For Participants in India: Monday to Friday @ 9 PM – 10 PM (IST)
For Participants in the US: Monday to Friday @ 11:30 AM – 12:30 PM (EST)
For Participants in the UK: Monday to Friday @ 4:30 PM – 5:30 PM (BST)
What students have to say about Joseph:
|
⭐️ Excellent teaching style with strong industry knowledge. The trainer made Prompt Engineering and LLM testing easy to understand and implement — Smith ⭐️ Excellent teaching style with deep industry knowledge. The trainer made Prompt Engineering and AI response validation simple to understand. Real-time project explanations were highly valuable. I gained practical confidence in AI automation testing.— Pooja ⭐️Excellent support throughout the course with clear explanations. AI testing strategies were taught with real-world use cases. — Olivia ⭐️ The trainer has exceptional knowledge in AI automation testing and explained every concept with clarity. The Playwright framework sessions were practical and highly engaging. Real-time examples made learning easy and effective. Doubt clarification was quick and very helpful. This course gave me strong confidence in AI QA automation— Harika ⭐️ Very supportive trainer with deep expertise in AI-driven automation testing. The sessions were interactive and focused on real industry scenarios. Very valuable learning experience. — John |
What will I learn by the end of this course?
• Master AI Testing Fundamentals and modern AI QA concepts
• Build automation using Playwright with TypeScript
• Learn Prompt Engineering and LLM response validation
• Perform API & UI Automation Testing for AI applications
• Implement JSON Schema Validation and AI scoring systems
• Work with Playwright MCP Integration for AI-assisted testing
• Build scalable automation frameworks using best practices
• Integrate CI/CD pipelines with GitHub Actions
• Automate AI Chatbot and Resume Analyzer testing projects
• Gain hands-on experience with real-time AI automation projects
• Learn advanced debugging and reporting strategies
• Build industry-ready portfolio projects for AI QA and SDET roles
Salient Features:
- 45 Hours of Live Training along with recorded videos
- Lifetime access to the recorded videos
- Course Completion Certificate
Who can enroll for this course?
• Manual Testers looking to move into AI Automation Testing
• Automation Test Engineers wanting to upgrade to AI-driven testing
• SDET Aspirants preparing for advanced automation roles
• QA Professionals interested in Playwright and TypeScript
• Software Testers wanting hands-on AI testing experience
• Developers exploring AI application testing frameworks
• Freshers seeking career opportunities in AI QA and automation
• Professionals interested in Prompt Engineering and LLM Validation
• Engineers looking to learn API & UI automation with real-time projects
• Anyone aiming to build a career as an AI QA Engineer or Advanced SDET
Course syllabus:
Module 1: AI Testing Foundation
🔹Introduction to AI QA Engineer
-
- What is AI QA?
- SDET vs AI SDET
- Traditional Testing vs AI Testing
- AI application ecosystem
🔹AI Testing Basics
-
- What is LLM?
- Prompt, Token, Context
- Hallucinations
- Deterministic vs Non-deterministic responses
🔹AI Testing Strategy
-
- Accuracy testing
- Relevance testing
- Safety testing
- Bias testing
- Response consistency testing
🔹Advanced Playwright Recap
-
- Playwright architecture
- Test runner
- Fixtures
- Hooks
- Advanced locators
🔹TypeScript for Frameworks
-
- Interfaces
- Types
- Classes
- Async/Await
- Utility methods
🔹Framework Setup
-
- Playwright installation
- TS configuration
- Environment variables
- Folder structure
- Base framework creation
🔹Mini Practice Project
-
- First AI test
- Capture AI response
- Basic assertions
- HTML report generation
Module 2: Advanced Playwright Framework
🔹Page Object Model
-
- POM design
- Reusable methods
- Login page
- Chat page
🔹 Component Object Model
-
- Chat components
- Upload components
- Common reusable UI modules
🔹 Test Data Management
-
- JSON test data
- Prompt datasets
- Dynamic data generation
- Negative datasets
🔹 Fixtures & Hooks
-
- Custom fixtures
- Global setup
- Before/After hooks
- Cleanup strategy
🔹 Assertion Strategy
-
- UI assertions
- API assertions
- Soft assertions
- Custom assertions
🔹 Debugging Playwright
-
- Trace Viewer
- Screenshots
- Videos
- Console logs
- Network debugging
🔹 Weekly Framework Project
-
- Framework integration
- Reporting
- Folder standards
- Final review
Module 3: Prompt Engineering for QA
🔹 Prompt Engineering Basics
-
- Good vs bad prompts
- Prompt structure
- Role-based prompts
- Clear instruction writing
🔹 Requirement to Test Cases
-
- Requirement analysis
- AI-generated test cases
- Positive scenarios
- Negative scenarios
- Edge cases
🔹 Prompt Testing
-
- Prompt injection testing
- Jailbreak testing
- Same prompt validation
- Multi-prompt testing
🔹 AI Response Validation
-
- Exact match validation
- Keyword validation
- Regex validation
- Length validation
🔹 JSON Schema Validation
-
- Structured AI outputs
- Schema validation
- Required fields
- Data type checks
🔹 AI Scoring System
-
- Accuracy scoring
- Relevance scoring
- Safety scoring
- Completeness scoring
- Threshold logic
🔹 Weekly Assignment
-
- Prompt dataset creation
- Response validation
- AI scoring
- Summary report generation
Module 4: Real-Time Project 1: AI Chatbot Testing
🔹 Chatbot Application Overview
-
- Chatbot workflows
- User journeys
- Risk areas
- Test strategy
🔹 Chatbot UI Automation
-
- Open chatbot
- Send prompts
- Capture AI responses
- Validate UI rendering
🔹 Functional Testing
-
- FAQ prompts
- Invalid prompts
- Empty prompts
- Support workflows
🔹 Context Memory Testing
-
- Multi-turn conversation
- Follow-up validation
- Context retention
- Context reset testing
🔹 Negative AI Testing
-
- Unsafe prompts
- Abusive prompts
- Prompt injection
- Harmful response validation
🔹 Chatbot API Testing
-
- Prompt API
- Response validation
- Status code validation
- Response time testing
🔹 Project Completion
-
- Test suite integration
- Failure screenshots
- Reports
- Final review
Module 5: Real-Time Project 2: AI Resume Analyzer Testing
🔹 Resume Analyzer Overview
-
- Resume upload flow
- AI scoring system
- Skill extraction
- JD matching
🔹 File Upload Automation
-
- PDF upload
- DOCX upload
- Invalid file testing
- File size validation
🔹 AI Output Validation
-
- Name extraction
- Skill extraction
- Score validation
- Missing skills validation
🔹 JD Matching Testing
-
- Resume vs JD validation
- Match score testing
- Recommendation validation
🔹 Resume Analyzer API Testing
-
- Upload API
- Analyze API
- Error handling
- Response validation
🔹 Report Download Testing
-
- Download reports
- File existence validation
- Content validation
- Format validation
🔹 Project Completion
-
- End-to-end automation
- AI scoring
- JSON schema validation
- Report generation
Module 6: AI Framework + CI/CD + Interview Preparation
🔹 AI Utility Functions
-
- Prompt builder
- Validator utilities
- Score calculator
- Report formatter
🔹 LLM-as-a-Judge
-
- AI validating AI
- Evaluation prompts
- Pass/fail reasoning
- Limitations
🔹 Flaky AI Test Handling
-
- Retry strategy
- Threshold validation
- Golden dataset
- Stable assertions
🔹 CI/CD Integration
-
- GitHub Actions
- Automated test runs
- Report publishing
- Failure screenshots
🔹 AI Debugging Workflow
-
- Trace analysis
- Screenshot analysis
- Console debugging
- Bug summary generation
🔹 Playwright MCP Introduction
-
- MCP basics
- AI-assisted browser testing
- Exploratory AI testing
- MCP limitations
🔹 Framework Cleanup
-
- Naming standards
- README creation
- Code cleanup
- Folder review
🔹 Resume Preparation
-
- AI QA resume points
- Project explanation
- GitHub portfolio
- LinkedIn optimization
🔹 Interview Preparation
-
- AI testing interview questions
- Playwright advanced questions
- Prompt engineering questions
- Framework discussions
🔹 Final Demo Day
-
- Chatbot project demo
- Resume analyzer demo
- Framework walkthrough
- Mock interview
FAQ’s –Next-Gen AI Automation Testing with Playwright & TypeScript
1. What is this course about?
This course covers AI-driven automation testing using Playwright, TypeScript, Prompt Engineering, LLM validation, API & UI automation, and real-time AI projects.
2. Who can enroll in this course?
Manual testers, automation engineers, SDET aspirants, developers, freshers, and anyone interested in AI automation testing can enroll.
3. Do I need prior Playwright knowledge?
Basic automation knowledge is helpful, but the course covers Playwright fundamentals to advanced framework development.
4. Will I work on real-time projects?
Yes, students will build AI Chatbot Testing and AI Resume Analyzer Automation Projects with practical implementation.
5. What technologies will I learn?
You will learn Playwright, TypeScript, Prompt Engineering, LLM Validation, JSON Schema Validation, MCP Integration, API Testing, and GitHub Actions CI/CD.
6. Will I get hands-on practice?
Yes, the course includes practical coding sessions, assignments, framework building, and project implementation.
7. Will interview preparation be included?
Yes, the course includes resume preparation, project explanation guidance, mock interview preparation, and advanced AI QA interview questions.
8. Will I learn CI/CD integration?
Yes, you will learn GitHub Actions integration for automated test execution and report publishing.
9. What projects will I complete?
You will complete AI automation framework development, chatbot testing automation, resume analyzer testing, scoring utilities, and reporting projects.
10. What career opportunities after this course?
You can apply for roles like AI QA Engineer, Automation Test Engineer, SDET, Playwright Automation Engineer, and AI Testing Specialist.
How can I enroll for this course?
OR
For any other details, Call me or Whatsapp me on +91-9133190573
