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Generative AI courses

1093 Courses

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California Institute of Technology

Generative AI for NLP

Learn Generative AI for NLP in hands-on, self-paced course with live support. Extract insights, automate processes, and generate text with AI.
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California Institute of Technology

Advanced AI Techniques for Product Marketing

Guide your marketing strategy from data exploration to campaign launch by leveraging generative AI best practices and prompt engineering techniques designed for product marketers.
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California Institute of Technology

AI Training for Product Professionals

Get the skills you need to streamline workflows and optimize product decision making through the use of generative AI and prompt engineering.
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California Institute of Technology

Generative AI For Business Leaders

Ideal for those without an analytics or data background, you’ll get a foundational understanding of how the technology works and how to use it to meet business objectives. By the end of this course you’ll be able to weigh the benefits of AI and gAI, as well as understand the limitations, tradeoffs, and legal and ethical implications.
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California Institute of Technology Southern New Hampshire University

Generative AI Database Design & Management with ChatGPT

Imagine designing databases that evolve with your business, anticipate future needs, and solve problems you haven't even encountered yet. This course teaches you to use AI as your intelligent design partner—creating database architectures neither human nor AI could achieve alone. You'll master AI-powered design techniques that transform traditional.
provider Coursera
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California Institute of Technology Southern New Hampshire University

Generative AI SQL Database Specialist with ChatGPT

Master the transformative integration of Generative AI and SQL databases to completely reinvent how organizations design, query, and visualize their data systems. This pioneering specialization equips you with the cutting-edge skills to lead database innovation—where SQL and AI converge to create capabilities that were previously unimaginable. As G.
provider Coursera
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California Institute of Technology Coursera

H2O.ai Agents : From Theory to Practice

H2O.ai Agents : From Theory to Practice is a comprehensive course that bridges theoretical understanding with practical implementation, guiding learners through the complete lifecycle of AI agents. You will start with core concepts by understanding the fundamental architecture of AI agents, how they combine large language models (LLMs), tools, and.
provider Coursera
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California Institute of Technology Coursera

Generative AI for Program Managers

Are you a program or project professional keen to harness generative AI (GenAI) to enhance decision-making, optimize workflows, and improve stakeholder engagement? This Generative AI for Program Managers specialization gives you the expertise to leverage AI-powered transformation to improve operational efficiency, mitigate risk, and enhance strateg.
provider Coursera
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California Institute of Technology Coursera

Generative AI in Finance

Course Description: This course provides a comprehensive exploration of Generative AI and its transformative impact on the financial sector. Learners will delve into foundational concepts, key AI models, and their applications across financial analysis, decision-making, forecasting, and compliance. With a focus on real-world case studies and hands-.
provider Coursera
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California Institute of Technology Coursera

Generative AI in Marketing

Course Description: Generative AI is revolutionizing the marketing landscape by automating creative processes, enhancing personalization, and optimizing campaigns at scale. This course provides a deep dive into Generative AI and its applications in marketing, focusing on the core principles, models, and tools that enhance content creation, customer.
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!