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Implementing AI in Software Testing | AI in Test Automation
CompTIA Certified Badge
AI for Software Testing: Integrate innovative AI-powered tools and techniques into your testing workflow, enhancing the quality and efficiency of your projects
ID:TTAI2140
Duration:2 Days
Level:Intermediate
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What You'll Learn

Overview
Objectives
Audience
Pre-Reqs
Agenda
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Overview

CompTIA Authorized Partner Badge

Learn how artificial intelligence is revolutionizing the software testing process and discover its value in enhancing the efficiency and accuracy of your projects. Smarter Software Testing with AI: Harness the Power of AI in Your Testing Workflow is a two-day, comprehensive course that delves into a broad spectrum of topics. This program includes an in-depth introduction to AI in software testing, advanced AI-powered testing tools, test data generation using AI, refined test case selection techniques, predictive defect identification, and sophisticated test automation strategies. You'll gain hands-on experience with innovative tools such as PyTest, PyUnit, BeHave Framework and LambdaTest.com through engaging labs designed to deepen your understanding and enhance your skills.

Throughout the course, you'll explore the multifaceted advantages of AI-powered testing, discovering how AI-driven techniques can not only improve test data generation and test case selection but also offer predictive insights into potential defects. This enables a proactive approach to software quality assurance, streamlining your testing process and ensuring the delivery of superior products. You'll engage in practical, hands-on labs, working with cutting-edge tools and the latest AI trends like OpenAI, ChatGPT, and AutoGPT, ensuring you're at the forefront of technological advancements in software testing.

By the end of this immersive course, you'll possess a comprehensive understanding of AI's transformative role in software testing, its numerous benefits, and its wide-ranging practical applications. Equipped with this knowledge and hands-on experience, you'll be prepared to confidently integrate AI-powered tools and techniques into your software testing workflow, significantly enhancing the quality, efficiency, and innovation of your projects.

Objectives

Working in an interactive learning environment, led by our engaging OpenAI expert you'll:

  • Understand AI's Role in Testing: You will develop a strong foundation in the basics of AI in software testing, including familiarity with leading AI-powered tools, to leverage AI for enhancing test efficiency and effectiveness.
  • Generate Superior Test Data with AI: You will master the art of using AI to create comprehensive and varied test data sets, ensuring your testing is thorough and your software's performance is robust.
  • Refine Testing with AI Insights: You will learn to use AI for smart test case selection and defect prediction, focusing your testing efforts where they are most needed and preemptively addressing issues to improve software quality.
  • Automate Tests Efficiently with AI: You will acquire skills to integrate AI with test automation, boosting your testing speed and reducing manual effort, by understanding and applying AI in continuous testing and integration.
  • Boost Performance & Security with AI: You will explore how AI can be instrumental in enhancing your software's performance and security, learning to identify and rectify potential vulnerabilities and performance issues effectively.
  • Embrace Cutting-Edge AI Tools & Trends: You will stay ahead of the curve by understanding and applying the latest AI tools and trends in your testing processes, ensuring you're equipped to innovate and lead in AI-driven testing scenarios.

Audience

Audience & Skill Level: This intermediate-level course is great for experienced software testers, QA analysts, test automation engineers, and developers seeking to expand their skill set by incorporating AI-driven testing techniques.

Pre-Requisites

In order to gain the most value from this course you should possess the following incoming skills 

  • Basic understanding of software testing concepts and the software development lifecycle (SDLC): 
  • Familiarity with basic Python or Java basics (for the scripting part of the labs) 
  • Basic understanding of Artificial Intelligence applications in business   

 

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Agenda

Day 1

Introduction to AI in Software Testing

  • Understand the basics and significance of AI in software testing.

Getting Started with AI in Software Testing

  • Advantages of AI-powered Testing
  • Exploring AI-powered Testing Tools
  • AI Testing Tools for Less Technical Testers
  • Quick Guide: Top Ten Tips to Integrating AI-Powered Testing
  • Additional Insights for Getting Started with AI-Powered Testing
  • Common Use Cases of AI in Software Testing: Technical & Business Users
  • Activity: Get familiar with the AI Testing Environment
  • Test Data Generation using AI
  • Learn to create realistic and diverse test datasets using AI.

Overview of Test Data Generation

  • Advantages of AI in Test Data Generation
  • Techniques for Test Data Generation using AI
  • Step-by-Step Guide to Creating Test Data
  • Tops Tips & Best Practices for Creating Test Data using AI
  • Activity: Generating and Analyzing Test Data using AI
  • Advanced Test Case Selection using AI
  • Dive deeper into the selection of test cases using AI to optimize testing efforts.

Quick Guide to Applying AI to Test Case Selection

  • Tips for Success Using AI Tools for Test Case Selection
  • Deerp Dive: Study of Test Case Selection
  • Top Tips & Best Practices for Integrating Predictive Insights into Testing Workflow
  • Activity: Using AI Tools for Test Case Selection and Prioritization
  • Advanced Activity: Integrating AI into Test Case Selection with Python
  • AI-Powered Test Execution and Monitoring
  • Understand how AI can automate test execution and provide real-time monitoring.

Exploring AI in Test Execution: Elevating the Test Platform

  • Real-time Test Monitoring with AI: Unveiling Insights as They Happen
  • Transforming Analysis with AI: Deepening Understanding Through Data
  • Types of Useful AI-Driven Data Reports for Testers
  • Activity / Option 1: Executing and Monitoring Tests using AI
  • Activity / Option 2: Executing and Monitoring Tests with AI Using Pytest
  • Ten Practical Tips for Enhancing Test Execution and Monitoring with AI

Day 2

Defect Prediction using AI

  • Master the techniques to predict defects using AI, enhancing software quality.

Deep Dive into Defect Prediction

  • Techniques for Defect Prediction using AI
  • Preventive Measures Based on AI Predictions
  • Activity: Predicting and Analyzing Defects using AI
  • Test Automation using AI
  • Learn advanced test automation techniques powered by AI to streamline your testing process.

Advanced Techniques for Test Automation using AI

  • Integrating AI with Existing Automation Frameworks
  • AI in Continuous Testing and Integration
  • Activity: Implementing an AI-Driven Automation Test Suite

AI in Performance and Security Testing

  • Explore how AI can enhance performance and security testing.

AI in Performance Testing: Techniques and Tools

  • Top Best Practices for Leveraging AI in Performance Testing
  • AI in Security Testing: Identifying Vulnerabilities
  • Top Best Practices for Leveraging AI in Security Testing
  • Case Studies: AI-Driven Performance and Security Improvements
  • Activity: Utilizing AI for Performance and Security Testing
  • Applying the Latest Tools & Trends
  • Get hands-on with the latest AI tools and trends to innovate your testing process.

Applying the Latest AI Tools to your Testing Efforts

  • Utilizing GPT Models in QA and Testing: An In-depth Exploration
  • Sample Prompts for Testers
  • Top Ten Common Pitfalls to Avoid when Applying GPT to Testing Processes
  • Activity: Implementing a Sample Test with GPT

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