Generative AI courses

658 Courses

ChatGPT与AIGC技术的前沿探索

探索ChatGPT和AIGC技术的前沿,通过现场直播课程获取深刻的见解。这些课程涵盖了人工智能和内容生成的最新发展、实际应用以及未来的发展趋势,为您揭示这些令人兴奋的技术的广阔可能性。由XuetangX提供的尖端课程适合对AI和生成内容充满热情的学习者。
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ChatGPT Masterclass: ChatGPT Guide for Beginners to Experts!

Generative AI Courses ChatGPT Courses Search Engine Optimization (SEO) Courses E-commerce Courses Content Creation Courses Join our ChatGPT Masterclass on Udemy to transform your understanding from beginner to expert. This course focuses on the powerful ChatGPT 4 and includes lessons on prompt engineering and leveraging generative A.
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ChatGPT, Midjourney, Firefly, Bard, DALL-E, AI Crash Course

Unlock the power of artificial intelligence with our intensive AI Crash Course. In just 15 minutes, you'll gain essential skills to start utilizing the most cutting-edge AI tools including ChatGPT, Midjourney, Google Bard, Adobe Firefly, and DALL-E. This course, provided by Udemy, is a top choice among Generative AI Courses and offers specializ.
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Ultimate AI Art Content Creation Course (Generative AI)

Unlock Your Creative Potential with AI Embark on a revolutionary journey in the realm of digital creativity with our Ultimate AI Art Content Creation Course, available exclusively on Udemy. This expansive program delves into the capabilities of generative AI, encompassing the creation of images, videos, audio, and textual content..
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ChatGPT, Midjourney, DALL-E 3 & APIs - The Complete Guide

Unlock the secrets of maximizing your productivity with our complete guide on ChatGPT, Midjourney, DALL-E 3, and APIs. Designed to elevate your skills, this course offers a deep dive into the world of AI with practical applications in various APIs. Gain expertise in prompt engineering, navigate the unique features of the Cursor IDE, and harness.
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Generative AI, from GANs to CLIP, with Python and Pytorch

Expand your knowledge and skills in artificial intelligence by diving into the world of generative models. Our Udemy course, "Generative AI, from GANs to CLIP, with Python and Pytorch," offers a comprehensive guide to understanding and implementing cutting-edge AI architectures. Designed for those passionate about AI development, this course.
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Digital Transformation and Industry 4.0 Masterclass

Enhance your understanding of digital trends with the "Digital Transformation and Industry 4.0 Masterclass." Designed for those eager to master the intricacies of cutting-edge technologies and their practical applications, this course offers comprehensive insights into Digital Transformation and Industry 4.0. Dive into value drivers and learn b.
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OpenAI & ChatGPT API's: Expert Fine-tuning for Developers

Join the "OpenAI & ChatGPT API's: Expert Fine-tuning for Developers" course to delve into the fascinating world of AI language models. Offered by Udemy, this program guides developers through the advanced techniques of fine-tuning the ChatGPT API, ensuring optimal performance in integrating AI into business applications. Enhance your skills i.
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ChatGPT Masterclass: The Ultimate Beginner's Guide!

Welcome to the ChatGPT Masterclass: The Ultimate Beginner's Guide! Transform your productivity tools, create streams of passive income, and embark on a journey of personal growth with the revolutionary capabilities of ChatGPT. This course is powered by Udemy and is specifically designed to introduce the applications of generative AI through.
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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!