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Generative AI courses

659 Courses

California Institute of Technology AWS Skill Builder

AWS SimuLearn: No-Code Insights Extraction Using Generative AI

AWS SimuLearn is an online learning experience that combines generative AI-powered simulations with hands-on practice. This program helps individuals convert business problems into technical solutions by simulating a dialogue between a customer and a technology professional. In this AWS SimuLearn assignment, you'll work on a real-world scenario t.
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California Institute of Technology Google Cloud Skills Boost

Incorporating Generative Features into Complex DFCX Agents

Incorporating Generative Features into Complex DFCX Agents - Google Cloud Skills Boost Course Title: Incorporating Generative Features into Complex DFCX Agents Description: In this course, you will learn how to integrate multiple advanced generative capabilities within a Dialogflow CX agent. University: Provider: Google Cloud Skill.
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California Institute of Technology AWS Skill Builder

AWS SimuLearn: Generative AI App for Teaching and Learning

AWS SimuLearn: Generative AI App for Teaching and Learning AWS SimuLearn is an online learning experience that pairs generative AI-powered simulations with hands-on practice to help individuals learn how to translate business problems into technical solutions through the simulation of dialog between a customer and a technology professional. AWS Si.
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California Institute of Technology Pluralsight

Create AWS Infrastructure as Code Templates Using Generative AI

Create AWS Infrastructure as Code Templates Using Generative AI The course will teach you how to integrate generative AI into your regular cloud development workflow. In this course, Create AWS Infrastructure as Code Templates Using Generative AI, you’ll learn to create a production-ready lambda application with.
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California Institute of Technology Pluralsight

Visualizing Data with Generative AI

Visualizing Data with Generative AI Visualizing Data with Generative AI This course will teach you how to leverage generative AI in producing meaningful and effective data visualizations. Data visualizations can be an effective way to communicate the meaning of data. They can also, unfortunately, be a really good way to distract and confuse y.
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California Institute of Technology Pluralsight

Data Analysis with Generative AI

Data Analysis with Generative AI | Pluralsight Working successfully with big data requires powerful tools and experience. This course, Data Analysis with Generative AI, will teach you how to incorporate the power of generative AI tools into your data analytics workflow to make you faster and more effective at what you do. Adding generative AI.
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California Institute of Technology Canvas Network

Course Enhancement with Generative AI

In this fully online, self-paced workshop, participants will explore a series of generative AI (GenAI) use case tutorials, interact with peers, and gain hands-on experience with prompting through a variety of GenAI platforms in the context of teaching and learning. Participants ultimately construct their own GenAI course enhancement plan t.
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California Institute of Technology Google Cloud Skills Boost

Incorporating Generative Features into Complex DFCX Agents

Incorporating Generative Features into Complex DFCX Agents Incorporating Generative Features into Complex DFCX Agents Join our comprehensive course where you will master the integration of multiple advanced generative capabilities within a Dialogflow CX agent. This essential learning opportunity, provided by Google.
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California Institute of Technology Google Cloud Skills Boost

Website Modernization with Generative AI on Google Cloud

Website Modernization with Generative AI on Google Cloud Enhance the navigation experience of your website by using generative AI to provide a better search experience for your users. In this course, you learn how to use Vertex AI Search to provide your website users a generative search experience enabling them to discover content offered.
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California Institute of Technology Pluralsight

Create Azure Resource Manager Templates Using Generative AI

Title: Create Azure Resource Manager Templates Using Generative AI Description: Learn to streamline your Azure deployments using cutting-edge AI tools. This course will teach you how to efficiently create and manage Azure Resource Manager templates with generative AI. Creating and managing Azure Resource templates can be time-consuming and pron.
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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!