An Introduction to Generative AI Concepts
Generative AI
| Intermediate
- 17 videos | 2h 38m 19s
- Includes Assessment
- Earns a Badge
This comprehensive course delves deep into the fascinating world of Generative AI. Through a combination of engaging lectures and hands-on practice, participants will gain an in-depth understanding of what generative models are, how they differ from other AI techniques, and the theories and principles underlying them. You will discover various types of generative models, such as generative adversarial networks (GANs) and variational autoencoders (VAEs), and explore the process involved in training these models. Then you will examine the strengths, limitations, and practical applications of generative models across various domains, such as image generation, text generation, and data augmentation. Next, you will learn how to evaluate the performance of generative models and focus on ethical considerations in generative AI and the potential societal impact of these technologies. Finally, you will have the opportunity to generate synthetic data using generative models for training and testing purposes and investigate the notion of responsible AI in the generative era. Upon course completion, you will be prepared not just to use these powerful tools, but to use them wisely and ethically.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this courseDefine generative ai and its key componentsDifferentiate between generative ai and other ai methods, showcasing their unique features and use casesIdentify the fundamental principles and theories that drive generative aiOutline the various tools, technologies, platforms, and communities that comprise the generative ai ecosystemDescribe generative models like gans (generative adversarial networks) and vaes (variational autoencoders), including their structure and functionOutline the process involved in training generative models, from data gathering to model deploymentProvide a critical assessment of the strengths and weaknesses of generative models for various applicationsEvaluate the potential benefits and hurdles of using generative ai across various domains
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Describe how to use generative models to generate synthetic data for training and testing purposesUse generative models to generate synthetic data for training and testing purposesOutline the potential biases, ethical considerations, and societal impact when designing and using generative aiProvide an overview of the appropriate metrics and methods to evaluate the performance and quality of generative modelsOutline the use cases and practical applications of generative ai across various industriesDescribe how generative ai has the potential to redefine creativity and the possible societal consequencesOutline the importance of responsible ai practices and guidelines in the era of generative aiSummarize the key concepts covered in this course
IN THIS COURSE
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1m 18sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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18m 17sAfter completing this video, you will be able to define generative AI and its key components. FREE ACCESS
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9m 41sUpon completion of this video, you will be able to differentiate between generative AI and other AI methods, showcasing their unique features and use cases. FREE ACCESS
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8m 21sIn this video, we will identify the fundamental principles and theories that drive generative AI. FREE ACCESS
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12m 47sAfter completing this video, you will be able to outline the various tools, technologies, platforms, and communities that comprise the generative AI ecosystem. FREE ACCESS
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12m 28sUpon completion of this video, you will be able to describe generative models like GANs (generative adversarial networks) and VAEs (variational autoencoders), including their structure and function. FREE ACCESS
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6m 17sAfter completing this video, you will be able to outline the process involved in training generative models, from data gathering to model deployment. FREE ACCESS
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12m 25sUpon completion of this video, you will be able to provide a critical assessment of the strengths and weaknesses of generative models for various applications. FREE ACCESS
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11m 55sAfter completing this video, you will be able to evaluate the potential benefits and hurdles of using generative AI across various domains. FREE ACCESS
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5mUpon completion of this video, you will be able to describe how to use generative models to generate synthetic data for training and testing purposes. FREE ACCESS
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7m 48sIn this video, you will learn how to use generative models to generate synthetic data for training and testing purposes. FREE ACCESS
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8m 40sAfter completing this video, you will be able to outline the potential biases, ethical considerations, and societal impact when designing and using generative AI. FREE ACCESS
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8m 47sUpon completion of this video, you will be able to provide an overview of the appropriate metrics and methods to evaluate the performance and quality of generative models. FREE ACCESS
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14m 41sAfter completing this video, you will be able to outline the use cases and practical applications of generative AI across various industries. FREE ACCESS
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6m 4sUpon completion of this video, you will be able to describe how generative AI has the potential to redefine creativity and the possible societal consequences. FREE ACCESS
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12m 58sAfter completing this video, you will be able to outline the importance of responsible AI practices and guidelines in the era of generative AI. FREE ACCESS
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52sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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