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Generative AI courses

1062 Courses

California Institute of Technology Coursera

Introduction to Generative AI in Healthcare

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California Institute of Technology Johns Hopkins University

Generative AI

Delve into the intricacies of Generative AI through this advanced course focusing on theoretical foundations and practical applications. This program, provided by Johns Hopkins University via Coursera, covers essential topics such as transformers, large language models, and symbolic AI, equipping learners with the knowledge to integrate these.
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California Institute of Technology Coursera

GenAI for Customer Support

Discover how cutting-edge Generative AI tools can transform customer service by delivering faster, more accurate, and personalized support. Envision a scenario where you can analyze a customer's history, detect an issue, and propose a solution in real-time—all in an instant. Generative AI empowers customer service teams to automate routin.
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California Institute of Technology Coursera

GenAI for Execs & Business Leaders: Formulate Your Use Case

As an executive or business leader, effectively integrating generative AI (genAI) into your organization is crucial. This concise course is designed to navigate the challenges of using genAI strategically, focusing on crafting impactful use cases for your business sector. Throughout the course, engage in interactive activities employing IBM’.
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California Institute of Technology Coursera

Introduction to Generative AI Marketing

Discover the transformative power of generative AI in marketing with our specialized course designed for marketing professionals and business leaders. This course offers a comprehensive introduction to generative AI, showcasing how it is revolutionizing the creation and personalization of marketing campaigns. Over a concise 3-hour session, you w.
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California Institute of Technology Coursera

Introduction to Generative AI in Finance

Are you aware that generative AI is rapidly reshaping the financial services landscape? This groundbreaking technology is transforming how we analyze markets, manage risks, and tailor financial products, opening up unprecedented avenues for efficiency and innovation in the finance sector. We've designed this concise course to equip finance profe.
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California Institute of Technology Coursera

Introduction to Generative AI in Human Resources

The "Introduction to Generative AI in Human Resources" course offers foundational insights into the revolutionary impact of AI technologies on HR functions. Designed to meet the evolving needs of HR professionals and business leaders, this course unlocks new opportunities for enhancing recruitment processes, boosting employee engagement, and i.
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California Institute of Technology Coursera

Introduction to Generative AI in Legal

Discover the transformative power of Generative AI in the legal sector with our comprehensive short course. According to a 2023 Goldman Sachs report, AI can automate 44% of legal tasks, significantly cutting down the time spent on research and drafting documents. As a legal professional, this means you can revolutionize your workflow, focus.
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California Institute of Technology CourseHorse

Introduction to Generative AI: Using Copilot for Microsoft 365 (Live Online)

Welcome to your gateway into artificial intelligence through Microsoft Copilot. This live online course is tailored for individuals eager to integrate AI into their everyday Microsoft 365 operations. Experience firsthand how Copilot seamlessly enhances your favorite tools like Excel, PowerPoint, and Outlook, streamlining your tasks from data ma.
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California Institute of Technology CourseHorse

Intro to Midjourney AI-Assisted Image Making (Live Online)

Unlock the potential of AI-assisted image creation in our engaging 1-Day workshop, "Intro to Midjourney AI-Assisted Image Making." Designed for artists, designers, and creatives, this online course delves into the innovative world of generative image making with Artificial Intelligence using Midjourney’s state-of-the-art tools. Throughout the.
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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!