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Generative AI courses

659 Courses

California Institute of Technology Udemy

Generative AI - Risk and Cyber Security Masterclass 2024

Welcome to the Generative AI - Risk and Cyber Security Masterclass 2024, your gateway to mastering the complexities of cyber security in the realm of Generative AI. This comprehensive course is designed to equip you with the knowledge and skills necessary to identify and mitigate risks associated with Generative AI technologies. Generative AI.
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California Institute of Technology Udemy

Amazon Bedrock, Amazon Q & AWS Generative AI [HANDS-ON]

Elevate your AI capabilities with a comprehensive course on Amazon Bedrock, Amazon Q, and AWS Generative AI. Perfect for beginners, this hands-on training requires no prior experience in AI or coding. Dive into practical learning with over eight use cases, exploring various AWS and AI technologies such as Agents, Knowledge Bases, Chatbots,.
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California Institute of Technology Udemy

Generative AI For Beginners with ChatGPT and OpenAI API

Unlock the potential of Generative AI with this beginner-friendly course, where you'll learn how to harness the capabilities of ChatGPT. Dive into the world of AI and explore automation using the OpenAI API. Perfect for those starting in AI, this course provides all the tools and knowledge needed to excel in the field. University: Provider.
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California Institute of Technology XuetangX

数字经济创新创业

Institution: XuetangX Categories: Artificial Intelligence Courses Fintech Courses Generative AI Courses Cybersecurity Courses Entrepreneurship Courses Blockchain Development Courses Data Analytics Courses Digital Economy Courses
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California Institute of Technology XuetangX

量子位——中国AIGC产业峰会

Join us at the 量子位——中国AIGC产业峰会, a pivotal conference presented by XuetangX, where leading experts delve into the cutting-edge advancements and trends in artificial intelligence and generative content creation within China's innovative tech ecosystem. This event is an essential resource for anyone interested in the future of AI and its.
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California Institute of Technology Coursera

H2O ai Large Language Models (LLMs) - Level 3

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California Institute of Technology Coursera

Designing with GenAI and Capstone Project

Immerse yourself in a comprehensive graphic design course that empowers you to stay ahead of industry trends by leveraging AI tools and crafting a standout professional portfolio. This course enables you to critically analyze competitors, delve into design trends, and complete a capstone project focused on enhancing your designs for a fictit.
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California Institute of Technology Coursera

H2O Gen AI Ecosystem Overview - Level 2

Expand your understanding of H2O's GenAI platform with the Ecosystem Overview - Level 2 course, presented by H2O's Sanyam Bhutani. This course offers an in-depth exploration of tools, applications, and methodologies designed for AI and ML within the H2O ecosystem. You'll learn efficient data preparation techniques, advanced model training, dep.
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California Institute of Technology Coursera

Foundations of AI and Machine Learning

Foundations of AI and Machine Learning Course - Coursera Enroll in the Foundations of AI and Machine Learning course on Coursera, designed to offer a deep dive into the essential components of AI & ML infrastructure. This comprehensive program covers key aspects such as data pipelines, model development frameworks, and deployment platforms, e.
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California Institute of Technology University of Michigan

Generative AI: Shaping Work and Tasks

Dive deep into the transformative potential of generative AI with our course, "Generative AI: Shaping Work and Tasks." While it's early to predict its full implications, recent trends highlight significant changes in sectors like education, marketing, and journalism. Join us to understand the diverse roles and responsibilities in today's job m.
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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!