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Generative AI courses

659 Courses

California Institute of Technology Trailhead

Get Started with Einstein Copilot

Get Started with Einstein Copilot Immerse yourself in the practical aspects of setting up, testing, and extending your conversational AI assistant within Salesforce. This course, brought to you by Trailhead, is specifically designed to enhance your skills in Generative AI, Customer Relationship Management, and Conversational AI. Whether you'.
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California Institute of Technology Pluralsight

The Data Sessions: Prompt Engineering for Creatives

The Data Sessions: Prompt Engineering for Creatives Creative work can be kick-started with the help of generative AI products and services. Learning to think of these services as new collaborators in your creative work will unleash new possibilities and better outcomes for you. As a person in a creative career, it might feel a little threatenin.
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California Institute of Technology Pluralsight

The IT Ops Sessions: Using Google Cloud’s Generative AI for IT Service Desk Automation

The IT Ops Sessions: Using Google Cloud’s Generative AI for IT Service Desk Automation Join our IT Ops session and discover how to harness Google Cloud’s generative AI services to automate IT service desk tasks through advanced chatbot technology. Our conference-style, short-form sessions provide in-depth insights without the need for a long co.
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California Institute of Technology Pluralsight

OpenAI Chat Completions API

OpenAI Chat Completions API Course | Pluralsight Chat Completions is the OpenAI API that empowers you to create chatbots and interactive conversational agents like ChatGPT. In this course, you will learn to harness the power of the Chat Completions API for building generative AI applications that leverage natural language for.
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California Institute of Technology Coursera

OpenAI for Beginners: AI Assistants for Project Managers

OpenAI for Beginners: AI Assistants for Project Managers In this 2-hour long project-based course, you will learn to create an AI assistant using OpenAI's playground UI, publish your AI application through Chipp.ai, and evaluate and refine your AI assistant. Ideal for those with a basic understanding of generative AI, web applications, and key p.
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California Institute of Technology AWS Skill Builder

AWS SimuLearn: Introduction to Generative AI

AWS SimuLearn: Introduction to Generative AI AWS SimuLearn is an online learning experience that pairs generative AI-powered simulations with hands-on practice to help individuals learn how to translate business problems into technical solutions through the simulation of dialog between a customer and a technology profession.
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California Institute of Technology AWS Skill Builder

AWS SimuLearn: Moderator for Generative AI Content

AWS SimuLearn: Moderator for Generative AI Content AWS SimuLearn is an online learning experience that pairs generative AI-powered simulations with hands-on practice to help individuals learn how to translate business problems into technical solutions through the simulation of dialog between a customer and a technology professional. AWS SimuLearn:.
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California Institute of Technology AWS Skill Builder

AWS SimuLearn: Moderate Generative AI Chat App Conversations

AWS SimuLearn: Moderate Generative AI Chat App Conversations AWS SimuLearn is an online learning experience that pairs generative AI-powered simulations with hands-on practice to help individuals learn how to translate business problems into technical solutions through the simulation of dialog between a customer and a technology professional. AWS.
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California Institute of Technology AWS Skill Builder

AWS SimuLearn: Improve Code Quality Using Generative AI

AWS SimuLearn is an online learning experience that pairs generative AI-powered simulations with hands-on practice to help individuals learn how to translate business problems into technical solutions through the simulation of dialog between a customer and a technology professional. AWS SimuLearn: Improve Code Quality Using Generative AI In t.
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California Institute of Technology AWS Skill Builder

AWS SimuLearn: Generative AI for Personalized Marketing

AWS SimuLearn: Generative AI for Personalized Marketing AWS SimuLearn is an online learning experience that pairs generative AI-powered simulations with hands-on practice to help individuals learn how to translate business problems into technical solutions through the simulation of dialog between a customer and a technology professional. AWS Si.
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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!