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Generative AI courses

659 Courses

California Institute of Technology Pluralsight

Create AI-assisted Product Documentation

Create AI-assisted Product Documentation | Pluralsight Product managers and designers often spend a significant amount of time crafting clear and comprehensive documentation. This course will explore how AI can help streamline this process, generating better product documentation using ChatGPT. Creating detailed and accurate product documentat.
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California Institute of Technology Pluralsight

Identifying Opportunities for Generative AI in Your Organization

Identifying Opportunities for Generative AI in Your Organization | Pluralsight Course Title: Identifying Opportunities for Generative AI in Your Organization Description: This course will teach you how to identify, evaluate, and implement generative AI opportunities within your company to achieve strategic business goals. I.
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California Institute of Technology Pluralsight

Building Data Science Skills with Generative AI

Building Data Science Skills with Generative AI Upgrade your data science skills with Generative AI tools. This course will teach you to integrate Generative AI into your workflow, enhancing efficiency and analytical precision. Data science is evolving rapidly, and staying ahead means embracing the latest AI advancements. In this.
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California Institute of Technology Pluralsight

Assessing Data Readiness for Generative AI

Assessing Data Readiness for Generative AI Generative AI solutions thrive on quality data, and the best data often comes from within your organization. This course, "Assessing Data Readiness for Generative AI," will guide you in evaluating your data's suitability for AI training. Start by understanding the importance of dat.
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California Institute of Technology Pluralsight

Creating Synthetic Datasets with Generative AI

Course Title: Creating Synthetic Datasets with Generative AI Description: This comprehensive course will teach you how to leverage Generative AI tools to produce quality synthetic datasets for testing, validation, training, and other data needs. There is a significant industry demand for synthetic data to support various applications like testi.
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California Institute of Technology Pluralsight

Documenting and Communicating a Generative AI Strategy

Documenting and Communicating a Generative AI Strategy This course covers the strategic implementation of generative AI in business operations. Learning how to document and communicate a generative AI strategy is essential for enhancing business operations and staying competitive. In this course, Documenting and Communicating a Generative AI St.
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California Institute of Technology AWS Skill Builder

AWS SimuLearn: Use Gen AI to Build an Image Recognition System

AWS SimuLearn: Use Gen AI to Build an Image Recognition System 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 dialogue between a customer and a technolog.
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California Institute of Technology AWS Skill Builder

AWS SimuLearn: Text-to-Image Creation Using Generative AI

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. In this AWS SimuLearn assignment, you will review a real-wor.
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California Institute of Technology AWS Skill Builder

Generative AI for Executives (Arabic)

Generative AI for Executives (Arabic) تقدِّم هذه الدورة التدريبية صورة عالية المستوى للذكاء الاصطناعي المولّد. يستكشف الطلاب المقصود بالذكاء الاصطناعي المولّد، وكيف يمكن أن يعالج مخاوف المسؤولين التنفيذيين والتحديات التي تواجههم، وكيف يدعم نمو الأعمال التجارية. ويتعلمون أيضًا كيف أن الذكاء الاصطناعي المولّد لديه القدرة على إحداث ثورة في العديد من.
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California Institute of Technology AWS Skill Builder

Introduction to Generative AI - Art of the Possible (Japanese)

Introduction to Generative AI - Art of the Possible (Japanese) Introduction to Generative AI - Art of the Possible (Japanese) コースでは、生成 AI とそのユースケース、リスクと利点について紹介します。コンテンツ生成の事例を通じて、可能性の技術を示します。このコースを修了すると、受講者は生成 AI、およびそのリスクと利点の基本を説明できるようになります。.
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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!