Portnov Computer School
Software quality engineers working across code, testing, and project dashboards

{ AI IN QA }

AI Tech Enhanced
QA Engineer Bootcamp

Real-World, nopCommerce Focus

AI-powered QA training built around a real-world testing project — from test strategy and documentation to BDD, Jira/Xray, automation and a final Capstone.

Format
Online
Time
9 AM – 11 AM
Time zone
Pacific Time
{ Book a Call } { View Curriculum }

10 Hands-On Sessions

Real nopCommerce Project

AI-Assisted Automation

Portfolio-Ready Capstone

{ TOOLS }

AI Tools.
Real QA Work.

Work with the AI tools used throughout the program.

01

OpenAI

02

Gemini

03

Grok

04

Copilot

{ COURSE OVERVIEW }

From First Prompt
to Working Automation.

  1. 01AI Setup
  2. 02Test Strategy
  3. 03Test Documentation
  4. 04Test Cases
  5. 05BDD
  6. 06Jira / Xray
  7. 07Automation
  8. 08Coverage & Risk
  9. 09Capstone
  10. 10Interview

{ CURRICULUM }

10 Sessions.
One Real-World
QA Journey.

Every session builds on the previous one — taking students from AI-assisted test planning through documentation, BDD, Jira/Xray, automation and a complete Capstone project.

Session 01

Why AI Matters for QA + AI Tool Setup + First Test Strategy

Objective

Understand why AI is critical for future QA, master basic AI tools, and generate your first real test strategy.

Topics Covered

  • Why AI-Enhanced QA is non-optional in modern software
  • Overview: ChatGPT, Gemini, Grok, Copilot, Codeium
  • Fundamentals of Prompt Engineering for QA tasks
  • Live Demo: nop-qa.portnov.com walkthrough

In-Class Hands-On

  • Create an AI workspace (ChatGPT + Gemini + Copilot accounts)
  • Craft prompts for generating test strategies.
  • Generate a functional and regression strategy for nopCommerce QA portal.

Mini-Project Deliverable

Submit 1 AI-generated test strategy document customized for https://nop-qa.portnov.com/.

Session 02

Preparing Test Documentation for AI + Full Test Plan Generation

Objective

Learn how to "feed" AI the right way to generate powerful, usable artifacts.

Topics Covered

  • How to prepare clear, AI-friendly test documentation
  • What AI needs: clear requirements, acceptance criteria, flows
  • How to structure documentation for maximum LLM output quality

In-Class Hands-On

  • Prepare basic business and functional requirement documentation for nopCommerce QA site.
  • Generate a detailed Test Plan from the documentation using AI.

Mini-Project Deliverable

Submit structured requirements + the AI-generated test plan for nop-qa.portnov.com.

Session 03

Generate Test Cases → BDD → Jira/Xray Integration

Objective

Turn test documentation into real test cases, convert them into BDD, and manage them in Jira/Xray.

Topics Covered

  • Generating context-aware test cases from requirements using AI
  • Best practices for BDD format (Gherkin syntax)
  • Exporting test cases to Xray-compatible format
  • Loading tests into Jira with Xray

In-Class Hands-On

  • Generate positive, negative, and boundary case test cases.
  • Convert test cases into BDD feature files.
  • Export AI-generated cases in Xray CSV format.
  • Load them into Jira using Xray import.

Mini-Project Deliverable

Jira Board with Test Plan and Test Cases for nop-qa.portnov.com fully loaded.

Session 04

Feeding Full Project Context to AI + Coverage Analysis

Objective

Feed complete system documentation + HTML app archives into AI to identify coverage gaps and optimize.

Topics Covered

  • Pull and archive nop-qa.portnov.com locally in HTML format
  • Upload entire web app + test documentation to AI
  • How to guide AI to "read" and cross-reference
  • Analyzing and optimizing test coverage

In-Class Hands-On

  • Feed project archive and documentation into ChatGPT/Gemini/Copilot.
  • Ask AI to find missing test cases and suggest new ones.
  • Optimize regression suite by converting cases into smart BDD format.

Mini-Project Deliverable

Regression Gap Report + optimized BDD test suite for nopCommerce QA.

Session 05

Starting Automation: AI-Driven Script Generation + Debugging

Objective

Use AI to generate and debug test automation scripts based on selected BDD scenarios.

Topics Covered

  • Selecting the best candidates for early automation
  • Setting up a basic WebDriver or Playwright base framework
  • Prompting AI to generate test automation scripts
  • Debugging scripts using AI suggestions

In-Class Hands-On

  • Select 5 core BDD scenarios.
  • Generate automation code using ChatGPT/Gemini/Copilot.
  • Debug with AI help until successful execution.

Mini-Project Deliverable

Working end-to-end automation of 1-2 BDD scenarios.

Session 06

Deeper Automation Sprint: Multiple Test Scenarios + Robust Debugging

Objective

Scale automation efforts, debug tricky cases, and polish testing techniques.

Topics Covered

  • Continue BDD to automation workflows
  • Debugging AI-generated flaky or partial scripts
  • Best practices for modular, clean test code

In-Class Hands-On

  • Automate 2 additional test cases.
  • Debug and stabilize scripts with AI suggestions.
  • Organize tests into feature-based folders.

Mini-Project Deliverable

A mini-regression automation suite (additional 2 test cases working end-to-end).

Session 07

Boundary Testing + Scenario Outline Automation

Objective

Generate boundary cases with AI, convert tests into Scenario Outlines, and data-drive your automation.

Topics Covered

  • How to create adversarial and boundary test data
  • Scenario Outline best practices in BDD
  • Feeding boundary data to tests automatically

In-Class Hands-On

  • Generate data sets using ChatGPT/Gemini/Copilot
  • Update BDD Feature files with Scenario Outlines
  • Inject boundary cases dynamically during test runs

Mini-Project Deliverable

1-2 Scenario Outlines covering critical areas like login, checkout, profile management.

Session 08

Capstone Project – Planning & Setup

Objective

Start building your final full-stack AI-enhanced QA solution for nop-qa.portnov.com.

Topics Covered

  • Scope definition for Capstone
  • Test Plan, Test Cases, BDD, Automation, Risk Reporting – all in one package

In-Class Hands-On

  • Create project backlog:
  • Test Plan → Test Cases → BDD → Jira Integration → Automation → Reporting

Capstone Deliverable (Begin Draft)

Clear project plan and first Test Strategy + Jira Test Plan loaded.

Session 09

Capstone Project – Execution

Objective

Deliver a complete AI-enhanced QA solution end-to-end.

Topics Covered

  • Best practices for managing QA projects
  • Rapid debugging, polishing, final reporting

In-Class Hands-On

  • Complete BDD-based automation suite.
  • Generate intelligent risk and coverage reports via AI.
  • Finalize Jira/Xray project dashboard.

Capstone Deliverable (Final)

Working automation framework + Jira reports + test documentation.

Session 10

Interview Prep with AI + Graduation

Objective

Prepare for real-world interviews and showcase your Capstone project.

Topics Covered

  • Common AI + QA interview questions (and how to dominate them)
  • Live mock interviews using AI feedback
  • How to present your Capstone project like a pro
  • Resume + LinkedIn optimization for AI-QA branding

In-Class Hands-On

  • AI-based mock interviews (using ChatGPT interview simulations)
  • Portfolio polishing session
  • Live demo of projects to peers

Graduation Deliverable

Publish your Capstone project on GitHub + LinkedIn. Practice interviews ready to land your next QA job.

{ WHAT YOU'LL WALK AWAY WITH }

Not Just AI Knowledge.
A QA Portfolio.

01

Real-world project experience

02

Free cutting-edge AI tools

03

Hands-on automation + Jira integration

04

Resume-ready Capstone project

Modern QA mindsets companies desperately need.

{ CONTACT }

Ready to Take
the Next Step?

Have questions about the program, schedule or enrollment?
Talk to the Portnov team.

Address

830 Stewart drive, #106,
Sunnyvale, CA 94085

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