Join

Generative AI courses

542 Courses

California Institute of Technology LinkedIn Learning

AI and Generative AI for Video Content Creation

Discover how AI is revolutionizing video content creation in this comprehensive course by LinkedIn Learning. Learn about the latest advancements and techniques in AI that are transforming video, audio, motion graphics, and visual effects. Perfect for professionals seeking to enhance their skills in: Artificial Intelligence Generative.
course image
California Institute of Technology LinkedIn Learning

Get Ready for Generative AI

Get Ready for Generative AI Course Title: Get Ready for Generative AI Description: Dive into the world of generative AI with this insightful course. Learn the fundamental concepts, explore new capabilities, and understand the emerging issues in the field of artificial intelligence. Provider: LinkedIn Learning Catego.
course image
California Institute of Technology AWS Skill Builder

AWS Flash - Introduction to Responsible AI

AWS Flash - Introduction to Responsible AI This course provides an overview of what responsible AI is and why it is important in the context of generative AI. Responsible AI refers to the development, deployment, and use of AI in an ethical, transparent, fair, and accountable manner. The course covers core dimensions of responsible AI; establish.
course image
California Institute of Technology AWS Skill Builder

AWS Flash - Generative AI in Action: Real-World Use Cases

AWS Flash - Generative AI in Action: Real-World Use Cases This course provides an overview of generative AI use cases and the business value they offer. It includes real-world applications for generative AI across major industries and case studies. Course level: Fundamental Duration: 75 min Activities This course includes presentations, r.
course image
California Institute of Technology AWS Skill Builder

AWS Flash - Chalk Talks: Amazon Q

AWS Flash - Chalk Talks: Amazon Q This course provides an overview of the impact of generative AI, as well as common risks and challenges in implementing GenAI applications. The course then dives into Amazon Q and walks through its core components. Course level: Intermediate Duration: 45 minutes This course includes slide content and demo.
course image
California Institute of Technology Pluralsight

AI-driven Competitive Analysis

AI-driven Competitive Analysis This course will teach you how to conduct competitive analysis using AI tools and help you prepare a report that shows you how they compare to your product. As product managers or designers, competitive analysis is a huge advantage to understanding how your product or business stacks against the comp.
course image
California Institute of Technology AWS Skill Builder

AWS SimuLearn: Set Up an ML Environment

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: Set Up an ML Environment In this AWS SimuLearn assi.
course image
California Institute of Technology AWS Skill Builder

AWS SimuLearn: Chatbots with a Large Language Model (LLM)

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 dialogue between a customer and a technology professional. In this AWS SimuLearn assignment, you will review a real-world.
course image
California Institute of Technology AWS Skill Builder

AWS SimuLearn: Build Apps Faster with Amazon CodeWhisperer

AWS SimuLearn is an online learning experience that pairs generative AI-powered simulations with hands-on practice. It helps individuals learn how to translate business problems into technical solutions through simulated dialogues between a customer and a technology professional. In this AWS SimuLearn assignment, you will review a real-world sce.
course image
California Institute of Technology Google Cloud Skills Boost

Intro to CCAI and CCAI Engagement Framework

Intro to CCAI and CCAI Engagement Framework | Google Cloud Skills Boost This introductory course dives into the wide array of solutions within the Contact Center AI (CCAI) portfolio and highlights transformative generative AI features. Participants will explore the CCAI go-to-market strategies and engagement models, while understanding the bus.
course image

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!