What you'll learn:
- Main Features of Google GEMINI AI
- Main Features of OPENAI CHAT GPT
- Setup CI/CD pipelines with AI
- Generative AI for Quality Engineering
- Create a full performance test framework with Jmeter in the cloud with CHATGPT
- Create a full API Testing test framework with Jmeter and RESTAssured in the cloud with Google BARD
- Setup test tools with Google BARD
- Improve efficiency of working with Google BARD
- Connect to CHAT GPT API
- Train your own instance of GPT
- Gen AI example 1 - Story Enhancement
- Gen AI example 2 - Self Healing Code
- Gen AI example 3 - Production Recursive Testing
- Gen AI example 4 - Self Service Bot
- Gen AI example 5 - Recommendation Engine for E-commerce
- Example of Different models and usage based on ML type
- Understand Machine learning
- Improve Test automation with ChatGPT and Google BARD
- How to use ChatGPT and Google BARD for Quality Engineering
This introductory course is designed specifically for Software Quality Engineers interested in leveraging the power of Generative AI to enhance their testing, automation, and productivity.
Throughout the course, participants will learn how to apply Generative AI techniques to automate the generation of test cases, simulate user behavior, create user stories, write better code, rapid start adoption of a new framework and generate test data. The course will provide a practical understanding of how AI can be used to improve software quality and boost productivity, rather than focusing on the underlying AI algorithms and models.
Topics:
Understanding Generative AI: An overview of Generative AI and its applications in software testing and quality assurance.
Automated Test Generation: Learn how to use Generative AI to automatically generate a variety of test cases, reducing manual effort and increasing test coverage.
APIAccess for Chat GPT and Google Bard: Understand how to call Bard and GPT with the help of customer made consumers
Automated User Story Creation: Understand how Generative AI can be used to generate user stories, helping to streamline the requirements gathering and software development process.
Test Data Creation: Learn how Generative AI can be used to generate test data, ensuring comprehensive and effective testing while saving time and effort.
Code Investigation: Discover how Generative AI can assist in investigating complex code, identifying potential issues, and understanding code dependencies.
Code Explanation: Learn how Generative AI can be used to explain code behavior, making it easier to understand complex code and improve code quality.
Boosting Productivity: Understand how these Generative AI techniques can be integrated into your existing workflows to boost productivity, improve software quality, and accelerate delivery times.
[Practical] See how to create a Performance testing Framework with CI/CD on cloud with AI
[Practical] Create an APITesting Framework with Java and RESTAssured with AI
[Practical] Code Quality Validation Framework for Java
See differences between CHATGPT and GOOGLEBARD
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