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Generative AI courses

1062 Courses

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!
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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.
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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.
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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.
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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.
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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.
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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.
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California Institute of Technology Udemy

Get AWS AI Certified: HandsOn,Quiz & Tests|Zero-to-Hero 2025

Get AWS AI Certified: Hands-On, Quiz & Tests | Zero-to-Hero 2025 Join our expertly designed course for a comprehensive preparation to achieve your AWS AI Certification. Benefit from hands-on experience through curated practice tests in collaboration with the Amazon Team. Fast-track your path to certification and aim to succeed in your first at.
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California Institute of Technology Udemy

Hallucination Management for Generative AI

Unlock the secrets to effectively managing hallucinations in language learning models (LLMs) and generative AI with this comprehensive course on Udemy. Delve into scientifically backed strategies that equip you with the necessary skills to handle and mitigate hallucinations. This course is perfect for anyone looking to enhance their understan.
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California Institute of Technology Southern New Hampshire University

Generative AI Cybersecurity & Privacy for Leaders: A Primer

Are you prepared to steer your organization into the future of cybersecurity, prioritizing privacy in an increasingly AI-centric environment? This primer provides a foundational understanding of generative AI, exploring its transformative possibilities alongside the cybersecurity and privacy risks it introduces. It empowers you to embrace AI’s.
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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!