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Get Acquainted with Generative AIArtificial Intelligence is reshaping our world like never before. Generative AI is a type of AI model that can create new content, from text to images and more. In this non-technical course, you will learn this emerging field's key concepts and how to prepare for a future where such AIs are pervasive.
Understand How Generative AI WorksYou'll start by comprehending how these models create content, where they fit into the machine learning landscape, and how they are developed. From gathering training data to evaluating and improving models, you'll learn what AI companies must consider and do to bring generative AI tools into the world.
Explore Key Legal and Ethical ConsiderationsGiven the power of generative AI, we will also consider how laws and ethics play into building and using these models. You'll learn how to avoid bias and apply generative AI in a responsible way.
Get the Right Mindset for Utilizing These ToolsFinally, you’ll look at the future of generative AI and how we can leverage and collaborate effectively with these tools. After this course, you, too, will be able to unlock the creative capabilities of generative AI. Let's go!
Introduction to Generative AIFree
Familiarize yourself with the concept of generative AI and its ability to create content is introduced, along with its real-world applications and limitations. You'll delve into the differences between traditional machine learning models, generative AI, and artificial general intelligence (AGI), and explore the key factors driving the development of generative AI.What is generative AI?50 xpGetting to know generative AI50 xpWorking with a generative AI model100 xpApplications of generative AI50 xpGenerative AI in the machine learning landscape50 xpPicking the right tool for the job100 xpDifferentiating generative AI from traditional ML50 xpMore dogs and GANs50 xpThe evolution of generative AI50 xpDriving the field forward50 xpTransformers50 xpGenerative AI breakthroughs100 xp
Developing Generative AI Models
In this chapter, we cover the essential steps in creating generative AI models: research and design, data collection, model training, and evaluation. We examine the significance of diverse datasets and advanced training techniques, as well as various evaluation methods, while discussing their strengths and limitations.
Using AI Models and Generated Content Responsibly
This chapter focuses on the responsible use of generative AI. We discuss the challenges and strategies to mitigate social bias, intellectual property and privacy issues, and ethical considerations to prevent misuse. We conclude by exploring the immense potential and risks of Artificial Generative Intelligence (AGI), along with the approaches to control its outcomes.Evaluating and mitigating social bias50 xpSources of bias50 xpDetecting and mitigating bias100 xpCopyright and ownership50 xpLegal and privacy considerations50 xpIdentifying IP ownership claims50 xpResponsible generative AI applications50 xpUsage principles50 xpImplementing responsible AI practices100 xpArtificial general intelligence (AGI)50 xpAGI characteristics50 xpAGI outcomes100 xp
Getting Ready for the Age of Generative AI
Chapter 4 examines the potential, impact, and integration of generative AI into human workflows. It discusses key contributors to AI development, from universities to companies, and explores societal adaptations to AI. It delves into AI's implications for productivity, job dynamics, education, media, entertainment, scientific advancements, and ethical considerations.Bringing new AI into old workflows50 xpLeveraging generative AI for data science100 xpDesigning a new marketing campaign100 xpProgress in generative AI50 xpTo open source or not to open source50 xpSuper Duper GANs100 xpPreparing for a future of generative AI50 xpGenerative AI in education50 xpThe value of skills in an AI world50 xpYou made it!50 xp