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Generative AI courses

1093 Courses

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California Institute of Technology Pluralsight

Generative AI for Customers

Generative AI is transforming the dynamics of business communication, and understanding its application is crucial. This comprehensive course offers you the ability to harness Generative AI to craft effective business communications swiftly. Join our course, "Generative AI for Customers," and start by learning how to create a "zeroth-dra.
provider Pluralsight
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California Institute of Technology Pluralsight

Integrating Generative AI for Developers

provider Pluralsight
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California Institute of Technology Pluralsight

Ensuring Interoperability in Generative AI Systems

Ensuring seamless interoperability in generative AI systems is essential as technologies advance and integrations increase in complexity. This course, Ensuring Interoperability in Generative AI Systems, equips you with the necessary skills to integrate AI models into enterprise applications while ensuring long-term compatibility. Initially, yo.
provider Pluralsight
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California Institute of Technology Pluralsight

Aligning Generative AI with Business Cases

Join the course "Aligning Generative AI with Business Cases" to master the art of integrating generative AI into your business framework. This course guides you through identifying optimal use cases and effectively applying Gen AI to suit your business needs. Initially, you'll learn to evaluate the potential and leverage of Generative AI, follow.
provider Pluralsight
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California Institute of Technology edX

Mastering Generative AI for Software Development

Do you want to enhance your software development career by leveraging the power of generative AI? This course explores the transformative applications of generative AI across the entire software development lifecycle. The course teaches how generative AI-based tools enable code generation, scripting, and program creation, boosting developer pr.
provider edX
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California Institute of Technology Google Cloud Skills Boost

Generative AI for Developers

Explore the cutting-edge realm of Generative AI with Google Cloud Skills Boost’s tailored learning path specifically crafted for professionals in app development, machine learning, and data science. With a strong emphasis on technical application, this course takes an in-depth look into concepts like Diffusion Models, BERT, and Transformer Mod.
provider Google Cloud Skills Boost
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California Institute of Technology Microsoft Learn

Operationalize generative AI applications (GenAIOps)

Operationalize Generative AI Applications (GenAIOps) Module 1: Plan and Prepare a GenAIOps Solution By the end of this module, you'll be able to: Identify use cases for Generative AI applications. Select a model for your Generative AI application. Understand what GenAIOps is and its impact on the app lifecycle..
provider Microsoft Learn
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California Institute of Technology ESSEC Business School

Artificial Intelligence in Financial Planning

Unlock the potential of Artificial Intelligence in Financial Planning with our specialized course. Dive deep into how AI tools and technologies are revolutionizing the financial industry through expertly designed modules. Enhance your skills and knowledge with insights into AI integration, innovative tools, and essential ethical considerations..
provider Coursera
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California Institute of Technology DataCamp

AI-Assisted Product Launch

Embark on an insightful journey with the AI-Assisted Product Launch project designed to empower electric vehicle (EV) manufacturers. Navigate the complexities of uncharted markets with confidence by harnessing the power of generative AI. This project delivers a comprehensive approach to creating a data-driven market entry plan that prepares yo.
provider DataCamp
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California Institute of Technology DataCamp

Building a Go-To-Market Strategy

Kickstart the launch of schedule.ai, an AI-driven shift-management tool, by crafting a robust go-to-market strategy utilizing generative AI. This project guides you through identifying the optimum industry for swift adoption and devising strategic sales lead-generation techniques. Engage with an AI chatbot to master planning promotional effort.
provider DataCamp

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!