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URL: https://www.coursera.org/learn/ethics-in-genai-for-software-engineering-training

⇱ Ethics in GenAI for Software Engineering Training | Coursera

Ethics in GenAI for Software Engineering Training

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Ethics in GenAI for Software Engineering Training

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Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

4 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Understand key ethical frameworks for responsible AI development

  • Identify and mitigate bias in AI-generated software code

  • Navigate legal considerations like data privacy, transparency, and licensing

  • Apply real-world case studies to build compliant and trustworthy GenAI systems

Details to know

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Assessments

6 assignments

Taught in English

Build your subject-matter expertise

This course is part of the AI-Powered Software Development Certification Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 2 modules in this course

This beginner-friendly course explores the ethical and legal foundations of using Generative AI in software engineering. Learn key ethical frameworks, understand common types of bias in AI-generated code, and explore their real-world impact on development. Delve into legal considerations like data privacy, transparency, explainability, and compliance. Through real case studies including racial bias in facial recognition and data breaches discover strategies to build fair, responsible, and legally compliant AI systems.

No prior AI ethics or legal knowledge is required. A basic understanding of software development is recommended. By the end of this course, you will be able to: - Explain core ethical frameworks guiding Generative AI development - Identify and mitigate bias in AI-generated software code - Understand legal risks around AI, including data privacy and licensing - Apply best practices to ensure transparency and regulatory compliance - Learn from real-world case studies to design trustworthy AI systems Ideal for software engineers, developers, and AI practitioners seeking to build ethical, bias-aware, and legally compliant GenAI applications.

Explore the foundations of ethics and bias in Generative AI for software engineering. Learn key ethical frameworks, identify types of bias in AI-generated code, and understand their impact on software development. Discover strategies to mitigate bias through real-world case studies, including racial bias in facial recognition and data privacy breaches. Gain the skills to build fair, responsible, and trustworthy AI-powered software systems.

What's included

8 videos1 reading3 assignments

8 videos•Total 41 minutes
  • Learning Objectives•4 minutes
  • What is Ethics in Gen AI?•6 minutes
  • Frameworks of Ethics•6 minutes
  • Bias in GenAI-Generated Code and Its Types•4 minutes
  • Impact of Bias in Software Developement•4 minutes
  • Strategies for Mitigating Bias•7 minutes
  • Case Study: Facial Recognition Software Used by Law Enforcement Exhibits Racial Bias in Identification•6 minutes
  • Case Study: Data Breach Exposing Personal Information Collected by an AI Application•4 minutes
1 reading•Total 10 minutes
  • Course Syllabus•10 minutes
3 assignments•Total 70 minutes
  • Assessment for Foundations of Ethics and Bias in Generative AI•40 minutes
  • Quiz on Ethics in GenAI Foundations•15 minutes
  • Quiz on Addressing Bias in GenAI Code and Decisions•15 minutes

Understand the legal implications and best practices for using Generative AI in software engineering. This module covers key ethical and legal considerations including AI transparency, data privacy, licensing, and compliance. Learn how to ensure explainability, preserve user privacy, and maintain continuous monitoring. Explore real-world examples and adopt best practices to build legally compliant, ethical AI systems.

What's included

10 videos3 assignments

10 videos•Total 45 minutes
  • Transparency and Explainability•6 minutes
  • Preserving Privacy•4 minutes
  • Continuous Monitoring and Evaluation•3 minutes
  • Collaboration and Openness•3 minutes
  • Overview of Ethical and Legal Considerations•8 minutes
  • AI Bias and Transparency•5 minutes
  • Data Privacy and It's Example•6 minutes
  • Licensing and Compliance•5 minutes
  • Best Practices for Ethical and Legal Compliance•3 minutes
  • Key Takeaways•3 minutes
3 assignments•Total 70 minutes
  • Assessment for Legal Implications and Best Practices in Generative AI•40 minutes
  • Quiz on Legal Implications in GenAI Application•15 minutes
  • Quiz on Ethical and Legal Considerations•15 minutes

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Frequently asked questions

This course is ideal for software engineers, developers, AI practitioners, and anyone involved in building or managing AI-powered software systems.

No prior experience is required. A basic understanding of software development is recommended to follow technical examples and case studies.

You’ll learn key ethical frameworks, how to identify and mitigate bias in AI-generated code, and how to ensure transparency, data privacy, and legal compliance in AI systems.

Yes, the course includes real-world case studies and scenarios such as racial bias in facial recognition and data breaches to help you apply ethical and legal best practices effectively.

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,