Generative AI: Fundamentals, Applications, and Challenges
This course is part of Responsible Generative AI.
This introductory course provides a solid foundation in generative artificial intelligence (AI), covering fundamental concepts, practical applications, and ethical challenges. You'll explore the differences between predictive and generative AI, understand the AI lifecycle, and learn about data training and fine-tuning processes. The course examines various use cases across business, operations, and society, while also addressing critical concerns like inaccuracies, bias, copyright infringement, and data protection. Designed for beginners, this course equips you with essential knowledge to navigate the rapidly evolving landscape of generative AI responsibly.
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What you'll learn
Understand the fundamental concepts and principles of generative AI
Differentiate between predictive and generative AI systems
Explore the complete lifecycle of generative AI development and deployment
Analyze various applications and use cases across different industries
Identify potential risks including inaccuracies, bias, and copyright issues
Evaluate data protection considerations and security vulnerabilities
Skills you'll gain
This course includes:
1.1 Hours PreRecorded video
4 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 3 modules in this course
This comprehensive course introduces students to the fundamentals of generative artificial intelligence, providing a balanced perspective on both its powerful applications and inherent challenges. The curriculum begins with core concepts, distinguishing between predictive and generative AI while exploring the complete AI lifecycle from data training to deployment. Students learn about various implementation approaches including system and user prompts, and examine real-world applications across industries. The course emphasizes responsible AI practices, covering critical issues such as output inaccuracies, data protection, bias, copyright concerns, security vulnerabilities, and the limitations of outdated training data. Through practical exercises and discussions, students develop the knowledge needed to evaluate generative AI systems critically and implement them ethically.
Introduction to the Course
Module 1 · 58 Minutes to complete
Use Cases of Generative AI
Module 2 · 21 Minutes to complete
Responsible Generative AI Concepts
Module 3 · 1 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Responsible Generative AI
Instructor
Leading Expert in AI Ethics and Data Science at the University of Michigan
Merve Hickok is a distinguished lecturer in data science ethics at the University of Michigan's School of Information and serves as the Responsible Data and AI Advisor at the Michigan Institute for Data Science. She is the founder of AIethicist.org, a platform dedicated to advancing understanding and implementation of ethical practices in artificial intelligence. With over 15 years of experience in senior roles within Fortune 100 companies, Merve has become a globally recognized expert in AI policy, ethics, and governance. Her work emphasizes the impact of AI systems on individual rights, democratic values, and social justice, making her a key figure in discussions surrounding responsible AI development.Merve's contributions to the field have been widely featured in prominent media outlets such as The Guardian, CNN, and Forbes. She is actively involved in shaping AI policy on a global scale, advising organizations like the European Commission and UNESCO. In addition to her teaching responsibilities, Merve has provided testimony to various governmental bodies, including the U.S. Congress, on matters related to AI governance. Her dedication to promoting ethical standards in technology has earned her numerous accolades, including recognition as one of the 100 Brilliant Women in AI Ethics™ and the Lifetime Achievement Award for Responsible AI Leader of the Year.
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Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.