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Generative AI courses

541 Courses

California Institute of Technology edX

Impact, Ethics, and Issues with Generative AI

Impact, Ethics, and Issues with Generative AI In this course, you will explore the impact of generative artificial intelligence (AI) on society, the workforce, organizations, and the environment. This course is suitable for anyone interested in learning about the ethical, economic, and social implications of generative AI and how generative AI c.
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provider edX
pricing Free Online Course (Audit)
duration 3 weeks, 1-3 hours a week
sessions On-Demand
California Institute of Technology Coursera

Setting a Generative AI Strategy

In this course, we delve into the potential impact of Generative AI (GenAI) on various facets of business with a particular focus on customer value creation and productivity. We’ll review research from leaders in academia and industry to understand emerging thinking on GenAI’s business impact. Imagine a future where GenAI not only drives busin.
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provider Coursera
pricing Free Online Course (Audit)
duration 6-7 hours
sessions On-Demand
California Institute of Technology

Use Generative AI as Your Thought Partner

Use Generative AI as Your Thought Partner This lesson is part of the comprehensive program, Navigating Generative AI for Leaders. In this session, you'll explore how Coursera CEO, Jeff Maggioncalda, employs generative AI models to become a more effective leader. Jeff will delve into his AI setup, including model choices, and provide practical pr.
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California Institute of Technology Coursera

Navigating Generative AI Risks for Leaders

Navigating Generative AI Risks for Leaders This comprehensive course delves into the various risks and concerns associated with Generative AI. Topics include business model risks, inaccuracies in AI-generated content, and significant data security and privacy issues. It emphasizes the crucial role of the CEO in understanding and addressing these.
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provider Coursera
pricing Free Online Course (Audit)
duration 3-4 hours
sessions On-Demand
California Institute of Technology

Elevating Businesses and Careers with Generative AI

Elevating Businesses and Careers with Generative AI In this course, you will discover the transformative impact of generative AI on businesses and professionals and how generative AI is elevating opportunities for businesses and professionals in different industries. This course is designed for anyone interested in learning about business and care.
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California Institute of Technology Coursera

Generative AI: Enhance your Data Analytics Career

University: Provider: Coursera Categories: Generative AI Courses, Data Visualization Courses, Prompt Engineering Courses Immerse yourself in the prospective domain of generative AI with this comprehensive course designed to enhance your data analytics career. Delve into fundamental concepts, models, tools, and the varied applications of gener.
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provider Coursera
pricing Free Online Course (Audit)
duration 13 hours
sessions On-Demand
California Institute of Technology Coursera

Generative AI: Boost Your Cybersecurity Career

This short course provides cybersecurity professionals and enthusiasts with the latest Generative AI tools to address complex cybersecurity challenges. The course focuses on combating the exploitation of undetected vulnerabilities for which organizations increasingly turn to Artificial Intelligence (AI) and Machine Learning (ML). Generative A.
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provider Coursera
pricing Free Online Course (Audit)
duration 10 hours
sessions On-Demand
California Institute of Technology Coursera  Specialization

Generative AI for Data Analysts

Generative AI for Data Analysts Generative AI for Data Analysts The demand for professionals with knowledge of artificial intelligence (AI) is on the rise. There is a revolution in the way organizations make decisions based on generative AI data analysis. This specialization brings forth real-world generative AI use cases and popular generative.
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provider Coursera  Specialization
pricing Paid Course
California Institute of Technology

IBM Generative AI for Cybersecurity Professionals

IBM Generative AI for Cybersecurity Professionals Generative AI skills are becoming an essential part of a cybersecurity professional’s toolkit. The US Bureau of Labor Statistics projects a 32% increase in the number of cybersecurity professionals needed through 2032, with a current median salary of $112,000. This Specialization is designed to b.
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California Institute of Technology edX

Models and Platforms for Generative AI

This course is designed for enthusiasts and practitioners who share an interest in the rapidly advancing field of generative AI. This course centers around the core concepts and generative AI models that form the building blocks of generative AI. You will delve into the concepts of deep learning and large language models (LLMs). You will learn a.
course image
provider edX
pricing Free Online Course (Audit)
duration 3 weeks, 1-3 hours a week
sessions On-Demand

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!