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Generative AI courses

1013 Courses

California Institute of Technology edX

Generative AI for Everyone

97% of employers expect to benefit from using generative AI (Source: Access Partnership survey for Amazon Web Services). Organizations need individuals who know how to automate tasks, speed up research, analyze data swiftly, and create original content using gen AI. This generative AI Professional Certificate is ideal for anyone looking to build i.
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California Institute of Technology Coursera

Smart Data Cleaning with Generative AI

Tired of spending hours on tedious data cleaning? Imagine if AI could handle the heavy lifting for you, turning days of work into minutes. From detecting errors to organizing vast datasets, Generative AI can not only save you time but also elevate your data quality to new heights. Dive into this course to learn how to transform data prep from a cho.
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California Institute of Technology Georgia Institute of Technology

ChatGPT for Educators

In this program, educators of all levels will learn how to adjust to a world in which conversational AI has become as common as search engines and smartphones. This emerging technology demands some adjustments on the part of educators to make sure our homeworks and tests remain valid assessments of student learning, but adjusting to its existence.
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California Institute of Technology AWS Skill Builder

Automating with AI/ML for Small Business Owners

This course was developed by members of AWS Technical Field Communities (TFC), an AWS community of technical experts. The content is intended to complement our standard training curriculum and augment your AWS learning journey.This course provides small business owners with a high-level overview of generative artificial intelligence (AI). Learners.
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California Institute of Technology edX

Generative AI Engineering

The gen AI market is projected to grow at an impressive 46% CAGR through 2030 (Statista). The demand for tech professionals skilled in generative AI engineering is skyrocketing! This Generative AI Engineering Professional Certificate gives aspiring generative AI engineers, AI developers, data scientists, machine learning engineers, and AI research.
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California Institute of Technology edX

IBM Applied AI Developer

92% of companies plan to increase their AI investments over the next three years (McKinsey). Talented AI developers are in high demand! This IBM Applied AI Developer Professional Certificate gives aspiring AI developers the job-ready skills to build AI-powered applications, virtual assistants, and chatbots employers are looking for in just 6 month.
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California Institute of Technology edX

Foundations of AI

71% of executives say they prefer to hire a candidate with AI skills (Forbes); the need to get up to speed with AI has never been more critical. This IBM Professional Certificate gives you a practical understanding of the core concepts and real-world application of AI, plus job-ready skills using gen AI in just 9 weeks. Whether you’re an experienc.
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California Institute of Technology edX

Generative AI for Business Leaders and Executives

Generative AI presents executives and business leaders with unprecedented opportunities to innovate and drive measurable business outcomes. This IBM Executive Generative AI program is designed for forward-thinking business executives, leaders, and decision-makers who want to stay ahead of industry trends and capitalize on AI's transformative poten.
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California Institute of Technology edX

Generative AI Fundamentals

Become proficient in Generative AI with this program that covers all the fundamentals. This program will allow you to get practical skills with major cloud providers like Azure and AWS as well as foundational knowledge on the core concepts you must know. Developed by industry experts, this program provides you with practical experience using vario.
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California Institute of Technology Northeastern University

AI Innovation in Healthcare

AI is transforming the landscape of healthcare by offering innovative solutions to improve diagnostics, personalize treatment plans, and streamline clinical workflows. This course from Northeastern University, available through Coursera, delves into the crucial role of AI in modern healthcare. Participants will learn how various data forms, f.
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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!