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Generative AI courses

1093 Courses

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California Institute of Technology Coursera

Snowflake Generative AI

Ready to kickstart or elevate your career in AI? Gain critical practical skills with the Snowflake Generative AI program. Whether you're a budding student, an emerging professional, or an experienced data specialist, this course equips you with the competitive edge needed to thrive in today's job market. This comprehensive program offers an imm.
provider Coursera
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California Institute of Technology Southern New Hampshire University

AI Agents in Java with Generative AI

AI agents signify the future of software, evolving from passive tools to proactive problem solvers. In this cutting-edge course, you'll master the art of building these agents using the enduring power of Java. Frameworks might come and go, but the principles you'll learn here remain invaluable. This course delves deep into Java-based agent ar.
provider Coursera
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California Institute of Technology Higher School of Economics

Enseñar con IA: herramientas

Enseñar con IA es un curso introductorio gratuito en formato MOOC dirigido a profesores y formadores interesados en integrar la inteligencia artificial en sus métodos de enseñanza. Guiado por Federica AI Tutor, este curso abarca los conceptos fundamentales de la IA, enfocado en la aplicación de herramientas generativas para enriquecer las act.
provider Coursera
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California Institute of Technology Pluralsight

Getting Started with Artificial Intelligence for Business

Elevate your business efficiency by learning to utilize Artificial Intelligence in your daily operations. The 'Getting Started with Artificial Intelligence for Business' course, offered by Pluralsight, will equip you with the skills to produce professional-quality deliverables rapidly through generative AI. Discover techniques to create pol.
provider Pluralsight
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California Institute of Technology Pluralsight

Enhancing Traditional ML with Generative AI

In the rapidly evolving field of artificial intelligence, understanding the interplay between emerging Generative AI capabilities and traditional machine learning approaches is pivotal. The Enhancing Traditional ML with Generative AI course by Pluralsight equips you with the expertise to leverage these technologies effectively. This.
provider Pluralsight
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California Institute of Technology Pluralsight

Generative AI for Improving Feedback

Enhance your feedback process with Generative AI without losing the human touch. This course, designed for busy leaders and professionals, teaches you to effectively integrate AI into your everyday feedback tasks. In this practical course, Generative AI for Improving Feedback, you'll discover how to use AI tools to draft superior feedback whil.
provider Pluralsight
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California Institute of Technology Pluralsight

Azure AI Fundamentals

Embark on a journey to design and build AI-powered applications with Microsoft's cutting-edge Azure AI services. The "Azure AI Fundamentals" course on Pluralsight provides you with the skills to swiftly develop and deploy revolutionary AI solutions. Begin your exploration of the Azure AI services landscape, which includes innovative offerin.
provider Pluralsight
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California Institute of Technology Pluralsight

Introduction to Generative AI vs. Traditional ML

In the course, "Introduction to Generative AI vs. Traditional ML," you'll gain the knowledge to evaluate, compare, and select the ideal AI strategy for your projects. Begin by exploring the basics of traditional machine learning, covering supervised, unsupervised, and reinforcement learning techniques. Progress to understanding the mechanics.
provider Pluralsight
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California Institute of Technology Coursera

Building Generative AI Apps to Talk to Your Data

Advance your skills in conversational AI by enrolling in this course where you learn to develop applications that facilitate natural language interaction with both structured and unstructured data. Building on the foundations laid in our Intro to GenAI course, this program delves deep into practical application development using Snowflake Co.
provider Coursera
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California Institute of Technology Coursera

Architecting AI Solutions – Scalable GenAI Systems

This course offers a comprehensive journey into architecting scalable and efficient Generative AI (GenAI) applications. It equips you with the skills to design, deploy, and optimize GenAI systems. Dive into the foundational knowledge of GenAI, exploring its evolution from traditional AI to modern architectures. Deepen your understanding of co.
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!