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Generative AI courses

659 Courses

California Institute of Technology Coursera

Generative AI for Executives and Business Leaders - Part 2

Generative AI for Executives and Business Leaders - Part 2 As an executive or business leader in your organization, integrating AI well is likely number one for your strategic priorities. In this short course, hear what IBM leaders think about the essentials when it comes to strategically integrating GenAI at scale cross-functi.
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California Institute of Technology Coursera

Multimodal Generative AI: Vision, Speech, and Assistants

Multimodal Generative AI: Vision, Speech, and Assistants We are introducing a new course to replace the "Coding with ChatGPT" course in the Generative AI specialization. This updated course will cover materials, models, and content released in 2024. Some of the new additions include material on using AI for image-to-text (vision), text-to-speech,.
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California Institute of Technology Coursera

Generative AI Content Creation

Generative AI Content Creation Dive into the innovative world of generative AI and discover how to harness its power using Adobe Firefly to elevate your creative projects. By the end of this course, you’ll be equipped with the knowledge and skills to revolutionize your design process, making you a pioneer in the digital landscape. Join us an.
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California Institute of Technology Coursera

Advanced Generative Adversarial Networks (GANs)

Advanced Generative Adversarial Networks (GANs) Embark on an enlightening journey into the realm of Generative Adversarial Networks (GANs), where you will master the art of AI-driven image synthesis. This course begins with a solid foundation, introducing you to the basic concepts and components of GANs, such as the Generator and Discriminator..
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California Institute of Technology Southern New Hampshire University

Generative AI and Model Selection

Generative AI and Model Selection | Southern New Hampshire University | Coursera Delve into the realm of generative AI and discover the intricacies of selecting the perfect model to suit your requirements with this hands-on course. You will develop a robust understanding of generative AI models, and examine various deployment options such as web.
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California Institute of Technology AWS Skill Builder

AWS Flash - Introduction to Responsible AI (Korean)

In this course, we briefly explain what responsible AI is and why it is important in generative AI. Responsible AI refers to developing, deploying, and using AI in ethical, transparent, fair, and accountable ways. The course covers key elements of responsible AI including fairness, explainability, privacy, robustness, governance, and transparen.
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California Institute of Technology University of California, Davis

AI for Knowledge Workers

Enroll Now - Enhance your skills in AI with the University of California, Davis through Coursera. This beginner-friendly course is your gateway to understanding AI, from Machine Learning to Generative AI, enabling you to transform your approach to both creative and critical thinking tasks in the workplace. Learn to harness AI technologies like.
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California Institute of Technology AWS Skill Builder

Princípios da engenharia de prompts (Português) | Foundations of Prompt Engineering (Portuguese)

Neste curso, você aprenderá os princípios, as técnicas e as práticas recomendadas para criar prompts eficazes. Este curso apresenta os elementos básicos da engenharia de prompts e avança para técnicas avançadas de prompts. Você também aprenderá a se proteger contra o uso indevido de prompts e a mitigar a interação com FMs. Nível do curso: int.
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California Institute of Technology Coursera

Interactive and Immersive Experiences with Generative AI

Embark on a transformative journey with the "Interactive and Immersive Experiences with Generative AI" course, your gateway to leveraging AI in the realms of creative industries and interactive media. Delve into a curriculum that seamlessly blends theoretical insights with practical demonstrations to empower your creative collaborations and re.
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California Institute of Technology SAP Learning

Generative AI at SAP

Discover how artificial intelligence (AI) transforms business processes with the 'Generative AI at SAP' course. This program provides a comprehensive understanding of AI's fundamental uses and benefits in a professional setting. Participants will explore different AI methodologies and study detailed use cases. Upon completion, attendees will gain.

A generative ai course is a fast-growing field of machine learning that can create new content, translate languages, write different types of creative content, and answer your questions in an informative way. It has great potential to revolutionize the way we create and use products.

A generative ai course refers to any artificial intelligence model that generates new data, information, or documents.

For example, many companies record their meetings, both live and virtual. Here are a few ways generative AI could transform these recordings:

And this is only a small part of all processes.

Generative AI Model Examples

There are a number of products using generative ai courses already available on the market – we'll give you a few examples below. The underlying principle of the generative ai courses at AI Eeducation varies depending on the specific model or algorithm used, but some common approaches include:

  1. Variational Autoencoders (VAEs) are a type of generative model that learns to encode input data into a latent space and then decode it back into the original data. The "variational" part of the name refers to the probabilistic nature of the latent space, allowing the model to generate a variety of outputs.

  2. Generative Adversarial Networks (GaN): GaNs consist of two neural networks, a generator and a discriminator, that are trained simultaneously through adversarial learning. The generator creates new data, and the discriminator evaluates how well the generated data matches the real data. The competition between the two networks causes the generator to improve over time in producing realistic outputs.

  3. Recurrent Neural Networks (RNNS) and Long Short-Term Memory (LSTM): These types of neural networks are often used to generate sequences such as text or music. RNNS and LSTM have memory that allows them to process a series of events over time, making them suitable for tasks where the order of elements is important.

  4. Transformer models: Transformer models, especially those with attention mechanisms, are very successful in various generative tasks. They can remember long-term dependencies and relationships in data, making them effective for tasks such as language translation and text generation.

  5. Autoencoders: Autoencoders consist of an encoder and a decoder, and they are trained to reconstruct the input data. Although they are primarily used for learning to represent and compress data, variations such as denoising autoencoders (e.g. in images) can be used for generative tasks.

An ai generative course involves feeding a model a large data set and optimizing its parameters to minimize the difference between the generated output and the real information. A model's ability to produce realistic and rich content depends on the complexity of its architecture, the quality and quantity of training data, and the optimization techniques used during training!