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Generative AI courses

1093 Courses

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California Institute of Technology DataCamp

Cleaning Data with Generative AI

Struggling with messy datasets that hinder your data analysis? Discover how generative AI can revolutionize data cleaning by addressing duplicates, nulls, and inconsistent formatting. We invite individuals new to data analytics to engage with a chatbot designed to streamline the data cleaning process. Gain hands-on experience by enhancing y.
provider DataCamp
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California Institute of Technology New York University (NYU)

AI in Digital Marketing

Course Title: AI in Digital Marketing Institution: New York University (NYU) Provided by: Coursera Course Overview: AI in Digital Marketing is crafted to arm digital marketers, brand strategists, and business leaders with the crucial AI tools and techniques needed today. Participants will delve into AI's vital role in boosting customer engag.
provider Coursera
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California Institute of Technology Pluralsight

Image Generation with DALL-E 3

Image Generation with DALL-E 3 Image-based generative AI allows the creation of stunning and useful images via prompts. This course will teach you how to generate high-quality images using the power of Generative AI with DALL-E. In this course, Image Generation with DALL-E, you’ll learn how to harness the power of generative AI for image creati.
provider Pluralsight
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California Institute of Technology Coursera

Creating Social Media Posts with GenAI: Mastering ChatGPT

Creating Social Media Posts with GenAI: Mastering ChatGPT Are you ready to elevate your social media game using the latest in generative AI? In today’s fast-paced digital world, creating engaging content that resonates with your audience is key to standing out. This Guided Project is designed to help social media managers, marketers, and cont.
provider Coursera
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California Institute of Technology AWS Skill Builder

AWS Flash - Automating with AI/ML for Small Business Owners

AWS Flash - Automating with AI/ML for Small Business Owners This course provides small business owners with a high-level overview of generative artificial intelligence (AI). Learners will explore the basics of generative AI technology and how to implement it to help their business expand into new markets, increase customer satisfaction, and enable.
provider AWS Skill Builder
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California Institute of Technology Coursera

Gemini in Google Drive - 简体中文

标题: Gemini in Google Drive - 简体中文 描述: Gemini for Google Workspace 是一个插件，用户可通过它来使用生成式 AI 功能。本课程通过视频课程、实操活动和实际示例，深入探讨了“Google 云端硬盘中的 Gemini”的功能。 学完本课程后，您将掌握相关知识和技能，能够自信地利用 Google 云端硬盘中的 Gemini 来改进工作流。 大学: 提供者: Coursera 分类: Cloud Computing.
provider Coursera
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California Institute of Technology Southern New Hampshire University

The History and Relevance of the Rise of Generative AI

The History and Relevance of the Rise of Generative AI Dive into the fascinating journey of artificial intelligence, from its theoretical beginnings to today's powerful generative models. This course offers a unique perspective on how AI has transformed over decades, highlighting the crucial developments in deep learning that paved the way for mod.
provider Coursera
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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.
provider Coursera
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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..
provider Coursera
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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.
provider Coursera

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!