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Generative AI courses

1020 Courses

California Institute of Technology LinkedIn Learning

Generative AI Imaging: What Creative Pros Need to Know

Generative AI Imaging: What Creative Pros Need to Know Explore the world of generative AI imaging and discover the essential tools and knowledge creative professionals need to thrive in this evolving field. This course, provided by LinkedIn Learning, covers a wide range of topics from Artificial Intelligence and Machine Learning to Digital Art,.
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California Institute of Technology LinkedIn Learning

Integrating Generative AI into the Creative Process

Integrating Generative AI into the Creative Process Learn how to incorporate generative AI into your creative process—particularly if you’re a creative working in business. Explore the intersection of artificial intelligence and creativity with this comprehensive course offered by LinkedIn Learning.
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California Institute of Technology LinkedIn Learning

Generative AI Skills for Creative Content: Opportunities, Issues, and Ethics

Generative AI Skills for Creative Content: Opportunities, Issues, and Ethics University: Provider: LinkedIn Learning Categories: Artificial Intelligence Courses, Ethics Courses, Generative AI Courses, Copyright Courses, Deepfakes Courses, Audio Generation Courses Gain a comprehensive understanding of the opportunit.
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California Institute of Technology LinkedIn Learning

Ethics in the Age of Generative AI

Ethics in the Age of Generative AI | LinkedIn Learning Course Title: Ethics in the Age of Generative AI Provider: LinkedIn Learning Hosted by: University Categories: Artificial Intelligence Courses, Ethics Courses, Generative AI Courses, Risk Management Courses, AI Governance Courses Learn why ethical considerations.
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California Institute of Technology LinkedIn Learning

Using AI Tools for UX Design

Using AI Tools for UX Design Learn how to utilize generative AI tools to elevate your UX design projects with expert insights from Eric Nordquist in this comprehensive LinkedIn Learning course. University: LinkedIn Learning Categories: Artificial Intelligence Courses, Generative AI Courses, ChatGPT Courses, Midjourney Courses, Image Generation.
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California Institute of Technology LinkedIn Learning

Using AI in the UX Design Process

Using AI in the UX Design Process Discover the transformative power of generative AI in the UX design process. This course delves into how AI technologies can speed up design workflows and boost creative output for designers. Ideal for those interested in Artificial Intelligence, Prototyping, Usability Testing, and UX Design.
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California Institute of Technology LinkedIn Learning

Generative AI and Predictive AI in the Cloud: Foundational Concepts and Scenarios

Generative AI and Predictive AI in the Cloud: Foundational Concepts and Scenarios Discover this easy-to-understand course for beginners that teaches the fundamentals of generative AI and predictive AI, as well as how they can relate to cloud computing. Provider: LinkedIn Learning Categories: Artificial Intelligence Courses, Machine Learning C.
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California Institute of Technology LinkedIn Learning

Generative AI, Recruiting, and Talent Acquisition

Generative AI, Recruiting, and Talent Acquisition | LinkedIn Learning Discover some of the most profound, long-lasting impacts of generative AI on recruiting and talent acquisition. Delve into how AI is reshaping the way organizations find and hire top talent with LinkedIn Learning's expert-led course.
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California Institute of Technology LinkedIn Learning

Generative AI for Digital Marketers

Generative AI for Digital Marketers Course Title: Generative AI for Digital Marketers Description: Discover the latest breakthroughs in generative AI, explore the opportunities and risks for marketers, and learn effective strategies to integrate AI tools into your creative workflows. Enhance your digital marketing skills with cutting.
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California Institute of Technology LinkedIn Learning

Prompt Engineering: How to Talk to the AIs

Prompt Engineering: How to Talk to the AIs | LinkedIn Learning Course: Prompt Engineering: How to Talk to the AIs Description: Enhance your AI capabilities by mastering the art of prompt engineering. Learn to design and optimize prompts for improved interactions with large language models. University: Provider: LinkedIn Learning.
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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!