Generative AI
Fundamentals, Applications, and Challenges
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.
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also dive into the general risks associated with this technology, including issues such as copyright infringement, outdated data, malicious attack surfaces, bias, and more.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.
What's inside
Syllabus
Introduction to the Course
Use Cases of Generative AI
Responsible Generative AI Concepts
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Syllabus
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Activities
Review "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
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Provide a foundational understanding of deep learning, a crucial component of generative AI.
View
Deep Learning
on Amazon
Show steps
-
Read Chapter 1: Introduction
-
Complete the exercises in Chapter 1
-
Summarize the main concepts in Chapter 1
Follow online tutorials on responsible AI practices
Show steps
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
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Select and follow tutorials that cover topics such as AI bias, fairness, and transparency
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Summarize and reflect on the key takeaways from the tutorials
Create a resource list on generative AI tools and techniques
Show steps
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
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Categorize and organize the resources into a comprehensive list
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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
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Develop practical skills in implementing and training generative AI models.
Browse courses on
TensorFlow
Show steps
-
Choose a generative AI framework (e.g., TensorFlow, PyTorch)
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Follow tutorials and complete exercises on using the framework
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Create a small generative AI project using the framework
Write a blog post on a generative AI application
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Demonstrate comprehension and ability to apply knowledge of generative AI applications.
Browse courses on
Generative AI Applications
Show steps
-
Choose a specific generative AI application
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Research the application and its benefits and challenges
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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
Show steps
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
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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
Show steps
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
Review "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
Show steps
Provide a foundational understanding of deep learning, a crucial component of generative AI.
View
Deep Learning
on Amazon
Show steps
- Read Chapter 1: Introduction
- Complete the exercises in Chapter 1
- Summarize the main concepts in Chapter 1
Follow online tutorials on responsible AI practices
Show steps
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
Show steps
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
Complete hands-on exercises on generative AI frameworks
Show steps
Develop practical skills in implementing and training generative AI models.
Browse courses on
TensorFlow
Show steps
- 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
Show steps
Demonstrate comprehension and ability to apply knowledge of generative AI applications.
Browse courses on
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
Show steps
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
Show steps
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
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