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via Udemy |
Go to Course: https://www.udemy.com/course/testing-quality-engineering-gen-ai-examples-gpt-bard/
Certainly! Here's a comprehensive review and recommendation for the Coursera course on Generative AI for Software Quality Engineers: --- **Course Review: Generative AI for Software Quality Engineers on Coursera** This introductory course is expertly tailored for Software Quality Engineers eager to harness the transformative power of Generative AI to elevate their testing, automation, and overall productivity. Designed with practicality in mind, the course avoids complex AI theory, instead focusing on actionable skills and real-world applications that can be immediately integrated into your workflows. **What You Will Learn:** - **Understanding Generative AI:** Gain a clear overview of what Generative AI is and explore its numerous applications within software testing and quality assurance. - **Automated Test Generation:** Learn techniques to automate the creation of diverse test cases, significantly reducing manual effort and expanding test coverage. - **API Integration:** Discover how to connect with AI models like ChatGPT and Google Bard, enabling seamless automation solutions. - **User Story Automation:** Understand how to generate meaningful user stories with AI, streamlining requirements gathering and development. - **Test Data Generation:** Leverage AI to produce realistic and comprehensive test data, saving time while improving testing effectiveness. - **Code Investigation & Explanation:** Utilize AI tools to analyze complex code, identify issues, and understand dependencies, enhancing code quality. - **Productivity Enhancement:** See how these AI-powered techniques can seamlessly augment your existing processes, boosting productivity and accelerating project delivery. **Hands-On Practical Applications:** The course includes practical segments such as creating a Performance Testing Framework with CI/CD on Cloud, developing an API Testing Framework with Java and RESTAssured, and building a Code Quality Validation Framework for Java. These real-world projects provide valuable experience and demonstrate how AI tools can be integrated into your testing infrastructure. **Additional Insights:** Participants will also explore advanced topics like Google Cloud AI solutions, self-learning AI agents, browser automation with AI, and collaborative agent frameworks, giving a broader perspective on AI's potential in software engineering. **Pros:** - Focused on practical skills rather than theoretical AI concepts - Covers relevant tools and frameworks used in the industry - Suitable for both beginners and experienced quality engineers - Emphasizes integration into existing workflows to boost productivity **Cons:** - May require some basic understanding of software testing and automation - Deep AI model details are not covered, as the focus is on application --- **Recommendation:** If you're a Software Quality Engineer looking to modernize your testing processes and explore the promising capabilities of Generative AI, this course is an excellent choice. Its pragmatic approach offers immediately applicable skills that can lead to more efficient testing, better code quality, and faster project delivery. Whether you're interested in test automation, data generation, or workflow enhancement, this course provides valuable insights and tools to stay ahead in the rapidly evolving landscape of software testing. --- **Final Verdict:** **Highly Recommended for quality assurance professionals seeking to integrate AI seamlessly into their testing ecosystems. Enroll now to unlock the future of software testing with Generative AI!**
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.API Access for Chat GPT and Google Bard: Understand how to call Bard and GPT with the help of customer made consumersAutomated 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 API Testing Framework with Java and RESTAssured with AI[Practical] Code Quality Validation Framework for JavaSee differences between CHATGPT and GOOGLE BARDGoogle Cloud AI solution with model training - Vertex AI AI-Powered Browser Automation - Master sophisticated AI operators for seamless, intelligent browser automation. Self-Learning AI Agents - Develop adaptive AI agents capable of self-improvement, continuous evaluation, and autonomous decision-making.Make agents communicate and solve issues with MSFT Autogen. An agent collaboration framework