Join

Generative AI courses

911 Courses

California Institute of Technology edX

Teaching and Learning in the Era of AI

Teaching and Learning in the Era of AI Learn to ethically and practically integrate AI in education with our comprehensive course. Designed for educators, administrators, and students, this course offers essential tools, strategies, and insights to transform teaching and learning for an AI-rich future. Gain tools, strategies, and insights to trans.
course image
California Institute of Technology University of Michigan

Learning Languages with AI

Learning Languages with AI Learning a new language can be exciting, but we don't always have the resources to push ourselves to the next level. In "Learning Languages with AI," you will learn how to enhance language learning with the help of generative AI tools. Identify your strengths and areas for improvement, then explore how you can responsi.
course image
California Institute of Technology Coursera

AI for Marketing: SWOT Analysis

AI for Marketing: SWOT Analysis In this course, learners of all AI comfort levels will learn the foundations of using generative AI for SWOT analysis. Whether you're an executive, a team leader, or a professional looking to upskill your AI literacy, this course will equip you with the tools and knowledge to leverage generative AI fo.
course image
California Institute of Technology University of Michigan

Using Generative AI for Learning Design Activities

Using Generative AI for Learning Design Activities | University of Michigan | Coursera In “Using Generative AI for Learning Design Activities,” you’ll experiment with how generative AI supports learning design tasks. Throughout the course, instructors will use an applied case study to illustrate how generative AI can enhance learning desi.
course image
California Institute of Technology Coursera

Generative AI in Marketing

Generative AI in Marketing Discover the transformative potential of Generative AI in the marketing landscape. This course offers an introduction to generative AI and explores its unique capabilities in the context of marketing. Learn to create compelling visual content and enhance customer engagement through advanced AI tools. Dive into the int.
course image
California Institute of Technology Indian Institute of Technology Guwahati

Generative AI for Healthcare Students and Professionals

Generative AI for Healthcare Students and Professionals This course aims to provide healthcare students and professionals with a solid foundation in how generative AI is used in their sector, adopting a balanced discourse of information. Participants will engage with case studies that analyze the current landscape of AI in various fields such as.
course image
California Institute of Technology Coursera

Capstone: Making the Case for AI

Capstone: Making the Case for AI Capstone: Making the Case for AI Put everything you learned in the AI in Marketing Specialization into practice in this capstone project. This course invites learners to delve into AI implementations in marketing—connecting to customer equity, showcasing generative AI's content production ca.
course image
California Institute of Technology Coursera

Driving Customer Equity with AI

Title: Driving Customer Equity with AI Description: This course covers how to drive customer equity and transform your marketing strategies using generative AI. Delve into the foundational components of customer equity and understand the impacts on long-term business success. Learn to evaluate marketing tactics through the lens of customer equit.
course image
California Institute of Technology University of Michigan

Generative AI as a Learning Design Partner

Generative AI as a Learning Design Partner In "Generative AI as a Learning Design Partner," you will explore opportunities and applications for generative AI in supporting and enhancing learning design activities and tasks. Discover how generative AI tools, like ChatGPT, can be utilized to create learning outcomes, draft course outlines, conte.
course image
California Institute of Technology edX

HP AI Teacher Academy

HP AI Teacher Academy Please stay on the AUDIT path for free access. Digital Promise and HP will provide a letter of completion with course hours upon completing the 5 modules for this course when using the free audit path. Additionally, you will not have a time limit to complete this course. There is no difference in content between the audit (fr.
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!