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Priyanka Mehta
To be successful in this course, you should have a basic understanding of software development practices, programming concepts, and technical documentation.
By the end of this course, you will be able to:
- Generate test cases and identify vulnerabilities using GenAI
- Apply AI to fix security issues across diverse codebases
- Automate API and project documentation with AI tools
- Create full-stack software documentation using GenAI workflows
Ideal for QA engineers, developers, and technical writers.
Register for this course and see more details by visiting:
OpenCourser.com/course/e21yv0/generative
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What's inside
Syllabus
Generative AI in Software Testing and Security
Explore how Generative AI transforms software testing and security in this practical module. Learn AI-driven techniques for automated test case generation and vulnerability detection across multiple programming languages. Understand how AI identifies, analyzes, and helps fix security flaws in code. Gain hands-on experience through demos that showcase AI-generated test cases and real-time vulnerability fixes.
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Syllabus
Generative AI in Software Testing and Security
Explore how Generative AI transforms software testing and security in this practical module. Learn AI-driven techniques for automated test case generation and vulnerability detection across multiple programming languages. Understand how AI identifies, analyzes, and helps fix security flaws in code. Gain hands-on experience through demos that showcase AI-generated test cases and real-time vulnerability fixes.
Read more
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Generative AI Course in Software Testing and Documentation.
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Career center
Learners who complete Generative AI Course in Software Testing and Documentation will develop knowledge and skills
that may be useful to these careers:
Software Development Engineer in Test
Software Development Engineer in Test
A Software Development Engineer In Test, or SDET, typically designs, develops, and maintains automated testing frameworks and tools. This course is exceptionally well-suited for an aspiring or current Software Development Engineer In Test, as it provides direct, actionable skills in leveraging Generative AI to automate critical testing processes. You will learn to generate test cases automatically and detect code vulnerabilities across various programming languages. The course specifically highlights how AI can identify and help fix security flaws in real time, which is paramount for creating robust and secure software. By mastering Generative AI workflows for testing, you enhance your ability to build more efficient, comprehensive, and intelligent automated testing solutions, making you an invaluable asset in modern software development teams.
Quality Assurance Engineer
Quality Assurance Engineer
A Quality Assurance Engineer is responsible for ensuring the quality of software products through thorough testing and defect identification. This course offers a significant advantage for a Quality Assurance Engineer by equipping you with cutting-edge Generative AI techniques to transform traditional QA practices. You will gain hands-on experience in generating test cases automatically and identifying vulnerabilities, leading to more comprehensive test coverage and earlier detection of issues. Furthermore, the course teaches how to apply AI to identify and address security flaws, enhancing the overall resilience of applications. By integrating Generative AI into your testing strategies, you significantly improve efficiency, accuracy, and the speed of quality assurance processes, which is crucial for delivering high-quality software in today's fast-paced development environments.
Technical Writer
Technical Writer
A Technical Writer plays a crucial role in creating clear, concise, and accurate documentation for software products, APIs, and processes. This course can significantly elevate an aspiring or current Technical Writer by teaching how to automate the entire documentation lifecycle using Generative AI tools. You will gain hands-on expertise in creating consistent project and API documentation, as well as developing end-to-end documentation for complex full-stack applications. This expertise is vital for improving efficiency, maintaining accuracy across large codebases, and delivering high-quality user and developer guides faster. Focusing on Generative AI workflows, this course directly addresses modern needs for scalable and rapid content creation, enabling you to produce exceptional documentation with unparalleled speed and consistency.
Automation Engineer
Automation Engineer
An Automation Engineer focuses on designing and implementing automated solutions for various processes, often within software development and operations. This course is an excellent fit for an Automation Engineer looking to expand their toolkit with Generative AI capabilities. You will learn how to automate critical stages of the software development lifecycle, including AI-powered software testing for test case generation and vulnerability detection, and the use of AI to identify and fix security flaws. Additionally, the course provides skills in automating project and API documentation with Generative AI tools. This holistic approach to automation across testing, security, and documentation enables you to build more intelligent, efficient, and comprehensive automation pipelines, driving significant productivity gains across an organization.
Vulnerability Assessment Analyst
Vulnerability Assessment Analyst
A Vulnerability Assessment Analyst specializes in identifying, evaluating, and reporting security weaknesses in systems and applications. This course offers highly relevant skills for a Vulnerability Assessment Analyst, particularly in its focus on leveraging Generative AI for security. You will learn how to use AI-driven techniques for vulnerability detection across multiple programming languages and understand how AI helps identify and fix security flaws in real time. This hands-on experience with AI-generated vulnerability detection can significantly enhance your ability to proactively uncover security risks, improve the speed and accuracy of assessments, and contribute to more secure software development practices.
Security Engineer
Security Engineer
A Security Engineer designs, implements, and monitors security measures to protect computer systems and networks. This course offers valuable insights and practical skills for a Security Engineer by focusing on Generative AI's role in proactive security. You will learn AI-driven techniques to detect code vulnerabilities across multiple programming languages and understand how AI helps identify and fix security flaws in real time. This hands-on experience in applying AI to security issues empowers you to build more resilient software, integrate advanced threat detection, and develop automated remediation strategies. Mastering these Generative AI applications for real-time security makes you a forward-thinking professional capable of fortifying software against evolving threats.
DevOps Engineer
DevOps Engineer
A DevOps Engineer focuses on bridging the gap between development and operations, emphasizing automation, continuous integration, and continuous delivery. This course aligns significantly with the goals of a DevOps Engineer by teaching how to automate critical stages of the software development lifecycle using Generative AI. You will learn AI-powered techniques for automated test case generation, real-time vulnerability detection and fixing, and the automation of project and API documentation. These skills are directly applicable to streamlining CI/CD pipelines, improving code quality, enhancing security, and ensuring comprehensive documentation is always up-to-date and consistent. This course helps you integrate cutting-edge AI automation into your DevOps practices, fostering a more efficient and reliable software delivery process.
AI Tools Integration Specialist
AI Tools Integration Specialist
An AI Tools Integration Specialist focuses on evaluating, implementing, and integrating artificial intelligence tools and platforms into existing workflows and systems. This course is directly relevant for an AI Tools Integration Specialist, as it provides practical, hands-on experience with Generative AI tools specifically for software testing, security, and documentation. You will learn to apply AI to generate test cases, detect and fix security flaws, and automate the creation of project and API documentation. This specialized knowledge enables you to identify appropriate Generative AI solutions, manage their deployment, and ensure their seamless operation within complex software development environments, ultimately driving efficiency and innovation across an organization's SDLC.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications and systems. This course offers highly relevant skills for a Software Engineer, enhancing your ability to build more robust, secure, and well-documented applications. You will learn to leverage Generative AI for automated test case generation and real-time vulnerability detection in your code, leading to higher quality and more secure products. Additionally, the course covers automating project and API documentation, which is crucial for maintainability and collaboration within development teams. By understanding and applying Generative AI at various stages of the software development lifecycle, this course helps you become a more efficient, productive, and forward-thinking developer in today's AI-driven landscape.
API Developer
API Developer
An API Developer specializes in designing, building, and maintaining Application Programming Interfaces, which enable different software systems to communicate. This course offers targeted benefits for an API Developer, particularly through its emphasis on Generative AI for documentation and testing. You will gain skills in automating API documentation with AI tools, ensuring accuracy, consistency, and rapid generation of crucial developer resources. Furthermore, the course's focus on AI-powered vulnerability detection and test case generation applies directly to ensuring the security and reliability of the APIs you develop. This expertise allows you to create high-quality, well-documented, and secure APIs more efficiently, which is essential for successful integration and developer adoption.
Full-Stack Developer
Full-Stack Developer
A Full Stack Developer works on both the front-end and back-end of applications, requiring a broad understanding of the entire development ecosystem. This course is particularly beneficial for a Full Stack Developer, as it specifically covers Generative AI workflows for creating end-to-end documentation for full-stack applications. You will also learn how AI can detect code vulnerabilities across multiple programming languages and generate test cases automatically, improving the quality and security of both your client-side and server-side code. This comprehensive training helps you deliver higher quality, more secure, and robustly documented full-stack solutions, streamlining your entire development process and enhancing your professional value.
Release Manager
Release Manager
A Release Manager coordinates the release process of software, ensuring that new features and updates are delivered smoothly and efficiently to users. This course may be useful for a Release Manager by providing insights into how Generative AI can automate critical aspects of the software development lifecycle that directly impact release readiness. Understanding AI-powered software testing for test case generation, real-time vulnerability detection, and the automation of project and API documentation can help you advocate for and implement processes that ensure higher quality, more secure, and well-documented releases. This knowledge can facilitate smoother deployments and reduce risks associated with software rollouts, ultimately improving the overall release cadence and consistency within an organization.
Solutions Architect
Solutions Architect
A Solutions Architect designs and oversees the implementation of complex IT systems, ensuring they meet business requirements and technical standards. While this course focuses on specific applications of Generative AI, the insights it provides may be useful for a Solutions Architect. Understanding how Generative AI can automate software testing, enhance security, and streamline documentation workflows equips you to design more robust, efficient, and secure software development lifecycles. This knowledge helps in proposing innovative solutions that leverage AI to improve product quality and team productivity. It informs strategic decisions about tooling and process optimization across the entire software development stack, preparing you to lead the integration of advanced AI capabilities within enterprise architectures. This role typically benefits from an advanced degree.
Technical Content Strategist
Technical Content Strategist
A Technical Content Strategist plans, develops, and manages the lifecycle of technical content, ensuring clarity, accuracy, and consistency across various platforms. This course may be useful for a Technical Content Strategist by introducing the transformative capabilities of Generative AI in content creation and management. You will gain an understanding of how AI tools can automate project and API documentation, ensuring consistent and accurate content for full-stack applications. This insight can help you develop more efficient content workflows, leverage AI for scalable content generation, and maintain a higher standard of information architecture. By exploring Generative AI workflows, you can devise innovative strategies to meet increasing demands for comprehensive and up-to-date technical documentation.
Product Manager
Product Manager
A Product Manager guides the strategy, roadmap, and feature definition for a product, acting as the liaison between business, design, and engineering teams. This course may be useful for a Product Manager seeking to understand how cutting-edge Generative AI can impact software product development. By learning how AI automates testing, identifies security vulnerabilities, and streamlines documentation, you gain crucial insights into improving product quality, reducing development costs, and accelerating time-to-market. This knowledge enables you to make informed decisions about feature prioritization, resource allocation, and overall product strategy, advocating for the integration of AI-driven tools to enhance development efficiency and deliver superior products to market. This role often benefits from an advanced degree.
For more career information including salaries, visit:
OpenCourser.com/course/e21yv0/generative
Reading list
We haven't picked any books for this reading list yet.
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Provides a thought-provoking exploration of the future of generative AI, discussing its potential benefits and risks. It is written by Gary Marcus, a leading researcher in the field.
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Explores the potential impact of generative AI on society, discussing how it could be used to solve social problems and improve quality of life. It is written by Kai-Fu Lee, a leading researcher in the field.
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Explores the relationship between generative AI and the creative process, discussing how generative AI can be used to enhance creativity. It is written by Margaret Boden, a leading researcher in the field.
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Explores the potential impact of generative AI on the law, discussing how it could be used to automate legal processes and improve access to justice. It is written by Ryan Abbott, a leading researcher in the field.
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Provides a practical guide to using generative AI, covering the different techniques and tools available. It is written by two leading experts in the field, Josh Patterson and Adam Gibson.
Explores the potential applications of generative AI in climate change, discussing how it could be used to model climate change and develop solutions. It is written by Andrew Ng, a leading researcher in the field.
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Provides a business-oriented perspective on generative AI, discussing its potential impact on industries and how companies can use it to gain a competitive advantage. It is written by three leading experts in the field, Thomas Davenport, Rajeev Ronanki, and Nitin Mittal.
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Explores the philosophical implications of generative AI, discussing how it challenges our understanding of mind and consciousness. It is written by Daniel C. Dennett, a leading philosopher in the field.
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Explores the potential applications of generative AI in healthcare, discussing how it could be used to improve patient care and accelerate drug discovery. It is written by Eric Topol, a leading researcher in the field.
Explores the potential impact of generative AI on the economy, discussing how it could be used to create new jobs and improve productivity. It is written by two leading experts in the field, Erik Brynjolfsson and Andrew McAfee.
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Provides a practical guide to agile testing. It covers a wide range of topics, from test planning and design to test execution and analysis. This book good resource for anyone who wants to learn more about how to test software in an agile environment.
Classic in the field of software testing. It provides a comprehensive overview of the principles and practices of software testing. This book good resource for anyone who wants to learn more about the foundations of software testing.
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Takes a practical approach to software testing, focusing on the skills and techniques that are essential for effective testing. It covers a wide range of topics, from test planning and design to test execution and analysis. This book good resource for anyone who wants to improve their software testing skills.
Provides a guide to exploratory testing. It covers a wide range of topics, from the principles of exploratory testing to the techniques that can be used to perform it. This book good resource for anyone who wants to learn more about exploratory testing.
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Practical guide to software documentation, covering the entire process from planning and writing to reviewing and publishing. It is an excellent resource for anyone who wants to learn how to write effective software documentation.
Provides a guide to selecting and using the right software testing tools for the job. It covers a wide range of topics, from the different types of software testing tools to the factors that should be considered when selecting a tool. This book good resource for anyone who wants to learn more about how to use software testing tools effectively.
Provides a practical guide to test automation. It covers a wide range of topics, from the principles of test automation to the techniques that can be used to implement it. This book good resource for anyone who wants to learn more about how to automate software tests.
Provides a comprehensive overview of the art of software testing. It covers a wide range of topics, from the principles of software testing to the techniques that can be used to perform it. This book good resource for anyone who wants to learn more about the foundations of software testing.
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Provides a comprehensive overview of software testing principles and practices. It covers a wide range of topics, from the principles of software testing to the techniques that can be used to perform it. This book good resource for anyone who wants to learn more about the foundations of software testing.
Provides a comprehensive overview of software testing, including both theoretical and practical aspects. It covers a wide range of topics, from test planning and design to test execution and analysis. This book good resource for anyone who wants to learn more about software testing, regardless of their experience level.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/e21yv0/generative
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Similar courses
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Level
Introductory
Via
Coursera
Institution
Simplilearn
Instructor
Priyanka Mehta
Session
October 27, 2025
- November 17, 2025
Language
English
Transcript
Español
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