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Merve Hickok

Rapidly evolving landscape of generative artificial intelligence (AI) means that both novice and skilled users alike should be aware of the proper applications and challenges of these powerful tools.

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Rapidly evolving landscape of generative artificial intelligence (AI) means that both novice and skilled users alike should be aware of the proper applications and challenges of these powerful tools.

In “Generative AI: Fundamentals, Applications, and Challenges,” you’ll discuss the potential benefits, uses, and challenges of a variety of applications for generative AI. Explore the impact these tools could have on business, operations, consumers, society, and the environment. Aspects of the course also dive into the general risks associated with this technology, including issues such as copyright infringement, outdated data, malicious attack surfaces, bias, and more. By participating in this course, you'll gain a strong baseline of knowledge for generative AI, one that will allow you to explore further considerations about its impact on businesses and society.

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Syllabus

Introduction to the Course
Use Cases of Generative AI
Responsible Generative AI Concepts
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Introduces applications of generative AI, which are in high demand in industry
Informs learners of emerging trends in generative AI, which are important to know about for all levels of experience
Examines common challenges associated with the use of generative AI, which can help students think critically about potential drawbacks
Teaches responsible use of generative AI, which is important to avoid unethical or harmful applications
Requires no prerequisite knowledge, making it a useful course for those with little to no experience in generative AI
Taught by Merve Hickok, an expert in the field, which signifies course quality and relevance

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Generative AI: Fundamentals, Applications, and Challenges with these activities:
Review "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
Provide a foundational understanding of deep learning, a crucial component of generative AI.
View Deep Learning on Amazon
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  • Read Chapter 1: Introduction
  • Complete the exercises in Chapter 1
  • Summarize the main concepts in Chapter 1
Follow online tutorials on responsible AI practices
Enhance understanding of ethical considerations and best practices in generative AI development.
Browse courses on Responsible AI
Show steps
  • Identify reputable sources for online tutorials on responsible AI
  • Select and follow tutorials that cover topics such as AI bias, fairness, and transparency
  • Summarize and reflect on the key takeaways from the tutorials
Create a resource list on generative AI tools and techniques
Foster a deeper understanding of available resources and tools for generative AI.
Browse courses on Generative AI Tools
Show steps
  • Research and identify generative AI tools and techniques
  • Categorize and organize the resources into a comprehensive list
  • Share the resource list with others in the learning community
Four other activities
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Complete hands-on exercises on generative AI frameworks
Develop practical skills in implementing and training generative AI models.
Browse courses on TensorFlow
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  • Choose a generative AI framework (e.g., TensorFlow, PyTorch)
  • Follow tutorials and complete exercises on using the framework
  • Create a small generative AI project using the framework
Write a blog post on a generative AI application
Demonstrate comprehension and ability to apply knowledge of generative AI applications.
Show steps
  • Choose a specific generative AI application
  • Research the application and its benefits and challenges
  • Write a blog post that clearly explains the application, its potential impact, and any ethical considerations
Participate in a study group to discuss generative AI use cases
Engage in collaborative learning and exchange ideas on practical applications of generative AI.
Browse courses on AI Applications
Show steps
  • Join or form a study group with peers
  • Prepare talking points and examples related to generative AI use cases
  • Facilitate or participate in discussions within the group
Contribute to open-source generative AI projects
Gain hands-on experience and contribute to the advancement of generative AI through open-source collaboration.
Browse courses on Generative AI
Show steps
  • Identify open-source generative AI projects
  • Choose a project that aligns with interests and skill level
  • Read the project documentation and contribute code or other resources

Career center

Learners who complete Generative AI: Fundamentals, Applications, and Challenges will develop knowledge and skills that may be useful to these careers:

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