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Generative AI courses

1093 Courses

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California Institute of Technology CodeSignal

Generative AI for Everyone in 2025

provider CodeSignal
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California Institute of Technology New York University (NYU)

AI Empowerment for Small Businesses

Welcome to our transformative course designed for small business owners and entrepreneurs eager to navigate the rapidly evolving world of Artificial Intelligence (AI). Discover AI's history, its significant evolution, and how it's reshaping industries to promote business growth and boost productivity. Throughout this course, explore the prac.
provider Coursera
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California Institute of Technology Coursera

Exam Prep AIF-C01: AWS Certified AI Practitioner

Artificial Intelligence (AI) enables machines to execute tasks requiring human-like intelligence such as decision-making and problem-solving. It includes subsets like Machine Learning (ML) for improving systems through data use without explicit programming, Deep Learning (DL) for advanced pattern recognition using neural networks, and Genera.
provider Coursera
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California Institute of Technology Coursera

NVIDIA: Large Language Models and Generative AI Deployment

Explore the intricacies of Large Language Models and Generative AI deployment with NVIDIA's comprehensive course, part of the Exam Prep for the NVIDIA-Certified Generative AI LLMs - Associate Specialization. This course blends theoretical insights with practical skills, covering all vital elements of Generative AI. Delve into essential top.
provider Coursera
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California Institute of Technology Coursera

GenAI for Legal Ethics and Practicality

Uncover the essentials of leveraging artificial intelligence in legal practice while adhering to evolving ethical standards with the GenAI for Legal Ethics and Practicality course. In today’s rapidly changing legal environment, integrating AI responsibly is crucial. This comprehensive course navigates the intricate intersection of AI and lega.
provider Coursera
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California Institute of Technology Coursera

GenAI for Prototyping Basics

In the fast-paced world of design and innovation, prototyping is crucial for swiftly transforming ideas into reality. This course leverages your existing knowledge of Generative AI, focusing on how AI platforms can streamline your prototyping process. You'll learn to use tools like ChatGPT, Canva, and Adobe Firefly to produce high-quality des.
provider Coursera
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California Institute of Technology Coursera

Exam Prep (NCA-GENL): NVIDIA-Certified Generative AI LLMs

The NVIDIA-Certified Generative AI LLMs - Associate Specialization is crafted for professionals in AI, machine learning, and deep learning who are eager to sharpen their skills in generative AI and large language models (LLMs). This program is designed to prepare participants to effectively design, build, optimize, and deploy generative AI sol.
provider Coursera
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California Institute of Technology Coursera

Generative AI: Transform Your Customer Support Career

Generative AI is revolutionizing customer service by enabling proactive interactions and support. As demand rises for professionals skilled in generative AI (GenAI), this course offers the vital GenAI competencies that businesses seek. Through this course, explore how GenAI can transform customer engagements and streamline support systems. Learn.
provider Coursera
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California Institute of Technology Coursera

Gemini in BigQuery

Embark on a transformative learning journey with our "Gemini in BigQuery" course. This pathway empowers you to exploit Gemini within the BigQuery ecosystem for sophisticated data and AI workflows. Begin with essential productivity enhancements and advance to crafting generative AI applications. By the end, achieve proficiency in Retrieval Aug.
provider Coursera
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California Institute of Technology Coursera

Generative AI for Customer Support

Generative AI for Customer Support | Enhance Your Career with Coursera According to Gartner, an impressive 85% of customer service leaders are gearing up to integrate conversational generative AI into their operations. As the business world increasingly adopts AI, our specialized program on Generative AI for Customer Support empowers customer su.
provider Coursera

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!