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Generative AI courses

1018 Courses

California Institute of Technology AWS Skill Builder

AWS AI/ML Essentials

Delve into fundamental concepts of AI and Machine Learning with our comprehensive course, "AWS AI/ML Essentials". Offered by AWS Skill Builder, this course is perfect for those looking to enhance their skills and understanding in the field of AI. With course material available in simplified Chinese (中文，简体), we ensure you can learn in the.
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California Institute of Technology edX

Generative AI for Business Leaders and Executives

Generative AI presents executives and business leaders with unprecedented opportunities to innovate and drive measurable business outcomes. This IBM Executive Generative AI program is tailored for forward-thinking business executives, leaders, and decision-makers who aim to stay ahead of industry trends and harness AI's transformative potential..
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California Institute of Technology edX

Generative AI Fundamentals

Engage in a program meticulously crafted by industry experts to provide you with the essential practical experience in Generative AI. This course covers an array of cloud services and tools, including AWS CodeWhisperer, SageMaker, Lightsail, and Azure OpenAI Service, aiming to enhance your capabilities with both Small Language Models (SLMs) and.
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California Institute of Technology edX

Mastering Generative AI for Data Engineering

Generative AI skills are highly sought after. A report by Ascend.io indicates that 89% of professionals utilize generative AI in some aspect of their work. According to ZipRecruiter, data engineers with these skills can earn an average salary of USD 115,000, reaching up to USD 179,000 annually. This course is crafted for current and aspiring dat.
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California Institute of Technology Coursera

GenAI for Legal Risk Management

In today's dynamic legal landscape, mastering risk management with AI not only enhances your skills but gives you a competitive edge. This course empowers legal professionals with state-of-the-art AI technologies to advance risk management practices significantly. Through this program, gain hands-on practical know-how in using AI for proa.
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California Institute of Technology Coursera

GenAI for Healthcare Automation

GenAI for Healthcare Automation Course AI in Healthcare, Healthcare Automation, Predictive Analytics, AI Ethics, Healthcare Technology Join us in the "GenAI for Healthcare Automation" course, where we move beyond the jargon to uncover the revolutionary impact AI is having on healthcare. Discover how artificial intelligence is enhancing patient car.
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California Institute of Technology Coursera

GenAI for Customer Journey Mapping

GenAI for Customer Journey Mapping - Coursera Discover the transformative power of Generative AI in customer journey mapping with our comprehensive course. Dive into leveraging AI tools such as ChatGPT to craft dynamic and predictive customer journeys that respond in real-time. By analyzing customer behavior patterns and anticipating needs, you'.
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California Institute of Technology Udemy

DALL-E 101: A Comprehensive Guide to Creating Art with AI

DALL-E 101: A Comprehensive Guide to Creating Art with AI - Udemy Course Immerse yourself in the world of AI artistry with our course, "DALL-E 101: A Comprehensive Guide to Creating Art with AI." Offered by Udemy, this course empowers you to harness the remarkable capabilities of DALL-E to generate bespoke artwork suited for any creati.
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California Institute of Technology Udemy

AI & LLM Engineering Mastery: GenAI, RAG Complete Guide

Embark on a comprehensive journey into the world of AI and LLM Engineering with Udemy's expert-led course, "AI & LLM Engineering Mastery: GenAI, RAG Complete Guide." This course covers everything from the basics to advanced engineering techniques, including fine-tuning of AI models, exploration of retrieval-augmented generation (RAG), and the in.
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California Institute of Technology Udemy

DeepSeek AI for Developers

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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!