This comprehensive Foundations of Ethical Generative AI course equips you with the skills to build responsible, transparent, and regulation-ready AI solutions. Begin by mastering core AI ethics principles, understanding ethical concerns, and learning data privacy frameworks like GDPR. Progress into solving transparency challenges by implementing Explainable AI (XAI) techniques and using tools like DALEX for model evaluation. Advance further into analyzing the regulatory, societal, and labor market impacts of Generative AI through real-world case studies in critical domains such as hiring, finance, and healthcare.
To be successful in this course, you should have a foundational understanding of AI concepts, data handling, and familiarity with programming or data science workflows.
By the end of this course, you will be able to:
- Understand Ethical AI Foundations: Learn ethical concerns, frameworks, and data privacy regulations
- Build Transparent AI Systems: Address the black box problem using Explainable AI (XAI) methods
- Analyze GenAI’s Societal Impact: Study real-world impacts and regulatory needs across industries
- Apply Responsible AI Practices: Implement ethical frameworks to drive trustworthy AI solutions
Ideal for AI practitioners, data scientists, developers, and compliance professionals focused on building ethical, scalable, and impactful Generative AI systems.
Master the foundations of ethical Generative AI with this comprehensive module. Learn key concepts, ethical concerns, and frameworks guiding responsible AI development. Explore critical data privacy principles, GDPR compliance, and challenges in data collection. Understand how to safeguard privacy in AI systems and apply ethical practices through real-world GenAI use cases and challenges.
Inclus
14 vidéos1 lecture3 devoirs
Afficher les informations sur le contenu du module
14 vidéos•Total 65 minutes
Learning Objectives•2 minutes
What Is Meant by Ethics of GenAI?•3 minutes
Ethical Concerns of GenAI•5 minutes
AI Ethics Framework•5 minutes
AI Ethics Framework: Key Requirements•6 minutes
Importance of Ethics in GenAI•3 minutes
Data Privacy for Ethical GenAI•5 minutes
Elements of Data Privacy•4 minutes
Challenges in Data Collection•6 minutes
Safeguarding Data Privacy•5 minutes
Data Privacy Laws and Regulations•5 minutes
Data Privacy Laws and Regulations: General Data Protection Regulation (GDPR)•6 minutes
Use Cases•5 minutes
Use Cases: Challenges•5 minutes
1 lecture•Total 10 minutes
Course Syllabus•10 minutes
3 devoirs•Total 70 minutes
Quiz on Understanding the Ethics of Generative AI•15 minutes
Quiz on Data Privacy and Ethical Challenges in GenAI•15 minutes
Assessment for Foundations of Ethical Generative AI•40 minutes
Transparency & Explainability in Generative AI
Module 2•2 heures à terminer
Détails du module
Explore transparency and explainability in Generative AI with this in-depth module. Understand the "black box" challenge in GenAI systems and its ethical implications. Learn about Explainable AI (XAI), how to implement it, and techniques for model transparency. Gain hands-on experience with tools like DALEX to interpret GenAI models and build trustworthy, transparent AI applications.
Inclus
8 vidéos3 devoirs
Afficher les informations sur le contenu du module
8 vidéos•Total 36 minutes
Black Box in GenAI System•4 minutes
How Is the Black Box a Challenge to Ethical GenAI?•5 minutes
Use Cases of GenAI Black Box•6 minutes
What Is XAI?•4 minutes
How to Implement XAI?•4 minutes
Model Transparency Techniques•3 minutes
XAI Tools•4 minutes
Scenario Using DALEX to Evaluate a GenAI Model•5 minutes
3 devoirs•Total 70 minutes
Quiz on The Black Box Challenge•15 minutes
Quiz on Explainable Artificial Intelligence (XAI)•15 minutes
Assessment for Transparency & Explainability in Generative AI•40 minutes
Regulatory, Societal, and Ethical Impacts of Generative AI
Module 3•2 heures à terminer
Détails du module
Understand the regulatory, societal, and ethical impacts of Generative AI in this insightful module. Explore why regulatory frameworks are essential as GenAI reshapes industries and the labor market. Analyze real-world case studies in hiring, finance, and healthcare to see how ethical AI practices can drive responsible innovation and protect critical sectors.
Inclus
5 vidéos3 devoirs
Afficher les informations sur le contenu du module
5 vidéos•Total 26 minutes
Need for Regulatory Frameworks•7 minutes
How Is GenAI Impacting the Labor Market?•6 minutes
Case Study on Hiring: Overview•5 minutes
Case Study on Finance: Overview•4 minutes
Case Study on Healthcare: Overview•3 minutes
3 devoirs•Total 70 minutes
Quiz on GenAI’s Impact and the Need for Regulation•15 minutes
Quiz on Importance of Ethical Generative AI in Critical Domains: Case Studies•15 minutes
Assessment for Regulatory, Societal, and Ethical Impacts of Generative AI•40 minutes
Simplilearn is a global leader in digital upskilling, offering highly specialized training in emerging technologies and processes shaping the digital economy's future. We focus on innovations transforming the digital landscape while significantly reducing costs and time compared to traditional methods. More than one million professionals and 2,000 corporate training organizations have benefited from our award-winning programs to achieve their career and business goals.
Pour quelles raisons les étudiants sur Coursera nous choisissent-ils pour leur carrière ?
Felipe M.
Étudiant(e) depuis 2018
’Pouvoir suivre des cours à mon rythme à été une expérience extraordinaire. Je peux apprendre chaque fois que mon emploi du temps me le permet et en fonction de mon humeur.’
Jennifer J.
Étudiant(e) depuis 2020
’J'ai directement appliqué les concepts et les compétences que j'ai appris de mes cours à un nouveau projet passionnant au travail.’
Larry W.
Étudiant(e) depuis 2021
’Lorsque j'ai besoin de cours sur des sujets que mon université ne propose pas, Coursera est l'un des meilleurs endroits où se rendre.’
Chaitanya A.
’Apprendre, ce n'est pas seulement s'améliorer dans son travail : c'est bien plus que cela. Coursera me permet d'apprendre sans limites.’
The Generative AI Ethics course is designed to help professionals understand and apply ethical principles in AI development. It covers topics like data privacy, transparency, regulatory frameworks, and Explainable AI to ensure responsible AI use.
What are the 5 Ethics of AI?
The five key ethics of AI typically include fairness, accountability, transparency, privacy, and safety. These principles guide responsible AI development and help ensure systems are unbiased, explainable, and aligned with human values.
Which certification is best for generative AI?
Top certifications for Generative AI include Simplilearn’s Generative AI programs, Google’s AI certification, and courses from DeepLearning.AI. The best option depends on your career goals, whether focused on ethics, engineering, or applied use cases.
Who is eligible for generative AI course?
Anyone with a basic understanding of AI or interest in ethical technology can enroll. The course is ideal for data scientists, developers, AI practitioners, and professionals in tech, compliance, or business roles aiming to work responsibly with AI.
When will I have access to the lectures and assignments?
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.
What will I get if I purchase the Certificate?
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
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.