Generative AI for QA Professionals and Software Testers

Name: Generative AI for QA Professionals and Software Testers
Rating: 4.4 (2796 reviews)

Generate Manual Test Cases and Selenium Scripts in automated manner using Generative AI on local system

Role Play

Created byRaghu The Security Expert

Last updated 2/2026

English

German [Auto],English [Auto],

What you'll learn

Understand AI and ML Fundamentals
Utilize Generative Models for QA (Manual and Automated) tasks
Learn Prompt Engineering for QA Professionals with real life examples
Create Spring Boot Rest API Application to generate selenium script and tests cases using Gen AI on local system
Learn to use Open source AI models

Course content

4 sections • 21 lectures • 2h 30m total length

Introduction and Agenda7:45
Learn the fundamentals of generative ai for qa, including models, tokens and embeddings, and prompt engineering, plus a case study automating qa tasks with jni and spring boot, without internet.

Agenda Items of this section2:30
Explore the fundamentals of generative ai, its examples and usage, then cover machine learning basics, ai models, and key models like GPT, Dall-E, and Codex.
Generative AI - Understanding and some use cases4:25
Learn the basics of generative AI, including how models generate images, text, music, and code across languages, with examples like Dall-E, ChatGPT, Copilot, and Tabnine.
Generative AI - Basic Terms7:55
Explore the basic terms of generative AI and artificial intelligence, including supervised, unsupervised, and reinforcement learning, and learn how algorithms train models from labeled and unlabeled data.
Understanding Model in layman terms5:26
Understand how a model comes from data collection, algorithm training, and refinements, culminating in a deployable model for tasks like text, image, or video generation.
What are Tokens and Embeddings in AI Models?8:10
Explore how tokens and embeddings enable ai models to process prompts. Learn about word, subword, and character token strategies and how embeddings feed neural networks to generate output.
Prompt Engineering Strategies for QA Engineers and Software Testers7:43
Learn prompt engineering for qa engineers and automation testers, focusing on input design, output guidance, model interaction, and fine tuning, with zero-shot, one-shot, few-shot, and chain-of-thought strategies.
Hands On: Prompt Engineering Live Examples for QA Engineers and Software Testers9:10
Explore hands-on prompt engineering strategies, zero shot, one shot, few shot, and chain of thought. Learn how QA engineers generate test cases for login functionality using ChatGPT with structured prompts.
Let's understand the ML type, Algorithm and Model in ChatGPT4:10
Explore how ChatGPT works by tracing its unsupervised and supervised learning from a large Common Crawl dataset, with reinforcement learning from human feedback shaping the GPT model.
Let's understand the ML type, Algorithm and Model in Dall-E3:19
Explore how DALL-E uses transformer-based neural networks and unsupervised pretraining to generate images. The lecture covers supervised fine-tuning and data gathering of text-image pairs for GPT-3-based image generation.
Let's understand the ML type, Algorithm and Model in Github Copilot3:50
Explore how GitHub Copilot relies on Codex, a transformer-based model trained with unsupervised and supervised learning on a vast corpus of publicly available code to generate code snippets.

Hands-On: Understand Case Study with using Gen AI for QA Engineering Tasks7:15
Automate QA workflows by using JNI modules to generate manual test cases and Selenium scripts from Jira acceptance criteria, orchestrated via a Spring Boot REST API.
Create an account with JIRA and create some issues in JIRA8:07
Create a Jira account, set up a software project, and add backlog items for login test cases and API test cases.
Hands-On: Install Ollama as a Prerequisite10:48
Install Ulama on Windows to run local language models, then use a Spring Boot API to fetch Jira acceptance criteria and generate test cases or selenium scripts.
Hands-On: Understand Repo for automated test case creation using GenAI6:12
Explore a Spring Boot repo that integrates Jira user stories with JNI modules to generate test cases using Ulama models. See how the API fetches acceptance criteria and generates tests.
Hands-On: Clone GitHub Repo for automated test case creation with GenAI - Part 18:49
Clone a GitHub repo locally and explore a Java Spring project that uses GenAI to generate test cases from Jira user stories, with VS Code and Gradle setup.
Hands-On: Clone GitHub Repo for automated test case creation with GenAI - Part 211:01
Demonstrate a JIRA integration that fetches a user story by key, extracts acceptance criteria, and feeds it to a GenAI model to generate tests.
Hands-On: Run Spring Boot Rest API App for automated test case creation - Part 114:33
Update Jira username, API token, and Jira API URL in application.properties, build and run the Spring Boot rest API app, and generate automated test cases for login and API stories.
Hands-On: Run Spring Boot Rest API App for automated test case creation - Part 24:29
Automate test case generation for the get all products API (ABC cop) with a 200 response, validating unique product objects with id, name, price, description, and at least five items.
Hands-On: Run Spring Boot Rest API App for selenium script creation12:13
Generative AI translates Jira acceptance criteria into a Java Selenium script for login flow, using Spring Boot and Mistral model.
QA Engineer 1:1 discussion with QA Manager on using Gen AI

Requirements

Basic Understanding of QA tasks
Fundamental Knowledge of Java

Description

Disclosure: This course contains the use of artificial intelligence.

Unlock the potential of AI in QA with our comprehensive course, "GenAI for QA and Software Testers." This program bridges the gap between AI theory and practical applications, equipping you with the skills to leverage Generative AI for automating and enhancing QA workflows.

Course Highlights:

Foundations of AI, ML, and Generative AI:
- Begin with a solid understanding of artificial intelligence, machine learning, and their types. Explore how models are developed and deployed, and learn the fundamentals of Generative AI, setting the stage for its application in QA.
Exploring Popular AI Models:
- Dive into the mechanics of widely used AI systems like ChatGPT, LLaMA, and others. Understand their architecture, capabilities, and how they can be leveraged for automating test case creation and other QA tasks.
Building a Spring Boot REST API Application:
- Develop a practical Spring Boot REST API app that integrates open-source GenAI models using the Ollama platform. This application will automate QA tasks such as manual test case creation and Selenium script generation.
Integrating with Jira for Real-World Automation:
- Learn how to make API calls to Jira to fetch acceptance criteria from sample user stories. See how these criteria are fed into GenAI models to automate manual testing and create Selenium scripts for test automation.
Hands-On Implementation of GenAI for QA:
- Implement GenAI solutions in real-world scenarios by building and testing an AI-integrated application. Develop expertise in using AI to generate accurate and efficient test cases, reducing manual effort and enhancing testing precision.
Automating Test Case and Script Creation:
- Automate the generation of manual test cases and Selenium scripts using AI models, streamlining the testing process and ensuring faster delivery cycles.

Who Should Enroll:

This course is tailored for QA engineers, software testers, and IT professionals looking to integrate Generative AI into their testing workflows. Whether you're new to AI or seeking to expand your knowledge, this course provides the practical skills needed to automate QA tasks and boost efficiency in software testing.

Join us to explore how Generative AI can transform your QA operations, enabling you to automate test creation and gain a competitive edge with cutting-edge AI-driven solutions!

Who this course is for:

QA Engineers
Software Testing Engineers/Professionals
Quality Analysts
Automation Engineers
QA Managers
IT Engineers

Generative AI for QA Professionals and Software Testers

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 8min

Generative AI Basics10 lectures • 57min

Case Study - Automated Test Case Creation using Gen AI from JIRA User Stories10 lectures • 1hr 23min

Next Steps1 lecture • 2min

Requirements

Description

Who this course is for: