Sign in Sign up

Generative AI courses

1093 Courses

course image
California Institute of Technology Udemy

Microsoft Copilot World (Microsoft 365, MS Purview) 25+ Hour

Join an engaging and comprehensive course on Udemy, where you'll dive deep into the world of Microsoft Copilot. With over 25 hours of content, this course provides a robust understanding of Microsoft technologies, including Microsoft 365, Microsoft Purview with a focus on securing generative AI, and explore tools like Azure Portal Copilot and.
provider Udemy
course image
California Institute of Technology AWS Skill Builder

Developing Generative Artificial Intelligence Solutions (Bahasa Indonesia)

Dalam kursus ini, Anda akan menjelajahi siklus hidup aplikasi kecerdasan buatan generatif (AI generatif), yang meliputi: Mendefinisikan kasus penggunaan bisnis Memilih model fondasi (FM) Meningkatkan kinerja FM Mengevaluasi kinerja FM Penggunaan dan dampaknya terhadap tujuan bisnis Kursus ini adalah pengantar untuk AI generatif, mendalami ko.
provider AWS Skill Builder
course image
California Institute of Technology AWS Skill Builder

Fundamentals of Machine Learning and Artificial Intelligence (한국어)

In this course, you'll delve into the fundamentals of Machine Learning (ML) and Artificial Intelligence, examining the relationships among AI, ML, deep learning, and emerging generative AI. You'll solidify your understanding of essential AI terms, setting a foundation for deeper exploration. Additionally, you'll learn about how different AWS s.
provider AWS Skill Builder
course image
California Institute of Technology AWS Skill Builder

Fundamentals of Machine Learning and Artificial Intelligence (简体中文)

在本课程中，您将学习机器学习 (ML) 和人工智能 (AI) 的基础知识。您将探索 AI、ML、深度学习和新兴的生成式人工智能领域之间的联系，充分理解 AI 的基础术语，为深入探究奠定基础。此外，您将了解使用 AI 和 ML 功能的精选 Amazon Web Services (AWS) 服务，并获得关于如何使用这些工具解决现实问题和推动各行业创新的实用见解。 课程级别：基础级 时长：1 小时.
provider AWS Skill Builder
course image
California Institute of Technology AWS Skill Builder

Exploring Artificial Intelligence Use Cases and Applications (Bahasa Indonesia)

Exploring Artificial Intelligence Use Cases and Applications (Bahasa Indonesia) Dalam kursus ini, Anda akan menjelajahi kasus penggunaan kecerdasan buatan (AI), machine learning (ML), dan kecerdasan buatan generatif (AI generatif) di dunia nyata di berbagai industri. Area-area ini meliputi pelayanan kesehatan, keuangan, marketing, hiburan, dan ba.
provider AWS Skill Builder
course image
California Institute of Technology Udemy

Generative AI For Leaders : The #1 surging skill for 2024

Udemy presents a cutting-edge course titled "Generative AI For Leaders: The #1 Surging Skill for 2024". This masterclass is designed to empower leaders and managers by enhancing their leadership and management skills through the strategic use of Generative AI. Explore a comprehensive curriculum that encompasses: Artificial Intelligence Cours.
provider Udemy
course image
California Institute of Technology Udemy

Generative AI Mastery With 15+ Real Time Projects

Generative AI Mastery With 15+ Real Time Projects - Udemy Enroll now in the Generative AI Mastery Course on Udemy and transform your machine learning skills with hands-on projects and expert guidance!
provider Udemy
course image
California Institute of Technology Udemy

Generative AI: Learn about the next AI frontier

Join the frontier of artificial intelligence with our comprehensive course on Generative AI. Understand the advantages, drawbacks, and unforeseen consequences that accompany this technology. Gain insights through specialized courses covering: Generative AI Courses Machine Learning Courses ChatGPT Courses DALL-E Courses Stable Dif.
provider Udemy
course image
California Institute of Technology AWS Skill Builder

Exploring Artificial Intelligence Use Cases and Applications (简体中文)

在本课程中，您将探索现实世界各行各业中人工智能 (AI)、机器学习 (ML) 和生成式人工智能的使用案例。这些领域包括医护、金融、营销、娱乐等。您还将了解 AI、ML 和生成式人工智能的能力和局限性、模型选择技巧和关键业务指标。 课程级别：基础级 时长：1 小时 注意：本课程具有本地化的注释/字幕。 旁白保留英语。要显示字幕，请单击播放器右下角的 CC 按钮。 课.
provider AWS Skill Builder
course image
California Institute of Technology AWS Skill Builder

Responsible Artificial Intelligence Practices (简体中文)

在本课程中，您将学习负责任的 AI 实践。首先，您将了解什么是负责任的 AI，学习定义与挑战，并探索其核心维度。 然后，深入开发负责任的 AI 系统，了解 AWS 提供的服务和工具，以及在模型选择和数据准备中的注意事项。 最后，您将了解透明且可解释的模型，探索其权衡考虑因素及以人为本的设计原则。 课程级别：基础级 时长：1 小时 课程内容：包含互动元素、文字.
provider AWS Skill Builder

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!