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Generative AI courses

1067 Courses

California Institute of Technology AWS Skill Builder

Introdução à IA generativa - A arte do possível (Português) | Introduction to Generative AI - Art of the Possible (Portuguese)

Introdução à IA generativa - A arte do possível (Português) | Introduction to Generative AI - Art of the Possible (Portuguese) O curso “Introdução à IA generativa - A arte do possível” oferece uma introdução à IA generativa, casos de uso, riscos e benefícios. Com a ajuda de um exemplo de geração de conteúdo, ilustramos a arte do possível..
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California Institute of Technology Pluralsight

Remaining Agile Through the Development of Generative AI

Remaining Agile Through the Development of Generative AI Course Title: Remaining Agile Through the Development of Generative AI Description: This course will teach you how to remain agile and open to change as your workforce transitions to using Gen AI tools and practices. In this course, Remaining Agile Through the Development of Generative AI, y.
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California Institute of Technology Pluralsight

Anthropic: Prompt Engineering for Cyber Security

Anthropic: Prompt Engineering for Cyber Security | Pluralsight As cybersecurity threats evolve, the need for innovative solutions becomes crucial. In this course, Anthropic: Prompt Engineering for Cyber Security, you'll learn to leverage the advanced capabilities of generative AI to improve your security strategies. First, you'll gain a fundam.
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California Institute of Technology Pluralsight

Generative AI for Project Managers

Generative AI for Project Managers | Pluralsight Course Generative AI is being rapidly adopted by organizations of all sizes and varying missions. Successful project managers must learn how this technology can best be put to use in achieving their goals. This course will help you do just that. First, you’ll explore some examples of how project lea.
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California Institute of Technology Codecademy

Pair Programming with ChatGPT Case Study

Pair Programming with ChatGPT Case Study In this case study, you will enhance your programming skills by collaborating with ChatGPT. Adopt the mindset of a novice developer and work alongside ChatGPT to solve coding challenges using Python. The primary focus will be on the Basta Fazoolin' project on Codecademy. Upon completing this case study,.
California Institute of Technology Codecademy

Debug Python Code with ChatGPT Case Study

Debug Python Code with ChatGPT Case Study Learn to resolve Python code issues using ChatGPT. This case study by Codecademy enables you to fix bugs, test, simulate, and optimize performance using generative AI. Develop your skills by adopting the mindset of a developer and applying best practices for debugging code with Chat.
California Institute of Technology Codecademy

Differentiate for Language and Reading Level With ChatGPT Case Study

Differentiate for Language and Reading Level With ChatGPT Case Study Use ChatGPT to create text at various levels of reading and language level. This can help streamline efforts for creation of educational material. This case study will help you develop your skills in using generative AI as a tool to create texts at different r.
California Institute of Technology Google Cloud Skills Boost

Generative AI Fundamentals - Locales

Generative AI Fundamentals - Locales This course, Generative AI Fundamentals - Locales, is designed specifically for non-English learners. If you prefer the course in English, please enroll in Generative AI Fundamentals. Earn a skill badge by completing the following courses: Introduction to Generative AI In.
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California Institute of Technology Google Cloud Skills Boost

Enterprise Search on Generative AI App Builder

Enterprise Search on Generative AI App Builder Enterprises of all sizes often struggle with making information easily accessible to both employees and customers. Internal documentation is frequently scattered across wikis, file shares, and databases. Similarly, consumer-facing sites tend to offer a vast selection of products, services, and informa.
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California Institute of Technology DataCamp

Understanding Prompt Engineering

Understanding Prompt Engineering Embark on an immersive journey to master ChatGPT, the groundbreaking conversational language model, and revolutionize your business and creative processes. This comprehensive course covers the essentials of prompt engineering, teaching you to construct clear, specific, and open-ended prompts, and advances into s.
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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!