Next-Gen Qa: Integrating Generative Ai In Software Testing

Test Faster. Smarter. Better with GenAI

What you'll learn

Understand the Fundamentals of Generative AI and Language Models

Develop Effective Prompt Engineering Skills

Apply Generative AI in the Software Testing Lifecycle

Evaluate AI Outputs with a Focus on Security, Ethics, and Practicality

Requirements

Basic Understanding of Software Development and Testing

General Technical Literacy

Description

Welcome to "Isha Training Solutions"** Please note: This course is a recording of live sessions, so you will hear student interactions throughout. We recommend watching the free preview videos first. If you like the content, you can then decide whether it’s worth your time and investment.**Generative AI in Software Testing: From Fundamentals to Applications is a comprehensive, hands-on course designed to equip software testers, QA professionals, and developers with the knowledge and skills to harness the power of Generative AI in modern testing workflows.Through engaging lectures and real-world examples, this course covers the foundations of artificial intelligence, large language models (LLMs), and prompt engineering. Participants will learn how to design effective prompts, understand AI model behavior, and apply these tools to various stages of the software testing lifecycle — from requirement analysis to test planning, execution, and reporting.With a strong emphasis on practical use cases, security considerations, and ethical AI usage, this course ensures participants are ready to confidently integrate AI tools like ChatGPT and JMeter into their daily testing activities for improved accuracy, efficiency, and insight.Students will also explore key AI parameters such as tokens, temperature, and context length, and how tuning them impacts results. The course highlights techniques like few-shot and zero-shot prompting, enabling more precise and context-aware test generation. Whether you're aiming to improve test coverage or reduce manual workload, this course provides the tools and techniques to take your QA practices to the next level using cutting-edge AI capabilities.

Overview

Section 1: Demo Introduction

Lecture 1 Gen AI Fundamentals Introduction - Demo video

Lecture 2 Demo_K

Section 2: Day 1

Lecture 3 Key Concepts And Terms -Day 1

Lecture 4 Day1_k

Section 3: Day 2

Lecture 5 How do LLMs work and their limitations and prompt engineering - Day 2

Lecture 6 day2_new

Lecture 7 Day2_k

Section 4: Day 3

Lecture 0 Limitations of LLM & Security risks-Day3

Lecture 8 Day3_k

Section 5: Day 4

Lecture 9 Language model parameters and Applications and use cases of AI

Section 6: Day 5

Lecture 10 Prompt components and Prompt frameworks

Section 7: Day 10_anitha

Lecture 11 Day 10

Section 8: demo by Kameswari

Lecture 12 demo

Section 9: Demo by Anitha

Lecture 13 Demo

Section 10: Day 6

Lecture 14 day6

Section 11: Genai_Kumarsirmachine

Lecture 15 video

Section 12: Day 6

Lecture 16 Part-1 Basic prompt structure and Prompt frameworks

Section 13: Day 7

Lecture 17 Part-2 Prompt frameworks and Examples

Section 14: Day 8

Lecture 18 Formatting and prompt parameters and Prompt tuning process

Section 15: Day 9

Lecture 19 Part-1 prompting techniques

Section 16: Day 10

Lecture 20 Part-2 prompting techniques examples

Section 17: Day 11

Lecture 21 Hallucination And Biases & Best practices/AI in Software Testing

Section 18: Day 12

Lecture 22 AI in Software Testing -Requirement analysis

Section 19: Day 13

Lecture 23 Part-1 Requirement analysis with AI conversational tools

Section 20: Day 14

Lecture 24 Test planning and Test strategy and approach preparation

Section 21: Day 15

Lecture 25 Part-1 Selection of different performance testing tools and Effort estimation

Section 22: Day 16

Lecture 26 Risk-based test prioritization and Identify different types of performance tests

Section 23: Day 17

Lecture 27 Test case development and Test case creation

Section 24: day18

Lecture 28 Part -1 Performance test script development

Section 25: Day 19

Lecture 29 Part-2 Test data creation

Section 26: Day 20

Lecture 30 Test environment set up and Test environment creation plan

Section 27: Day 21

Lecture 31 Part-1 Test environment selection and Verification of test environment

Section 28: Day 22

Lecture 32 Test execution

Section 29: Day 23

Lecture 33 Part-1 Performance bottlenecks, Defect reporting, Daily and weekly status

Section 30: Day 24

Lecture 34 Test cycle closure and Test results analysis

Section 31: Day 25

Lecture 35 Test metrics preparation and Test report creation

Software Testers and QA Engineers,Software Developers,Business Analysts and Product Owners,IT Professionals and Tech Enthusiasts,Students and Career Changers