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Generative AI courses

659 Courses

California Institute of Technology AWS Skill Builder

Fundamentos de machine learning e inteligência artificial (Português) | Fundamentals of Machine Learning and Artificial Intelligence (Portuguese)

Fundamentos de Machine Learning e Inteligência Artificial (Português) | Fundamentals of Machine Learning and Artificial Intelligence (Portuguese) Neste curso, você aprenderá sobre os fundamentos de machine learning (ML) e inteligência artificial (IA). Você explorará as conexões entre IA, ML, aprendizado profundo e o campo emergente da inteligência.
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California Institute of Technology Coursera

Introduction to AI and Machine Learning on GC - Português

Neste curso, apresentamos os recursos de IA e machine learning (ML) no Google Cloud que criam projetos de IA generativa e preditiva. Vamos conhecer as tecnologias, os produtos e as ferramentas disponíveis em todo o ciclo de vida de dados à IA, o que inclui os fundamentos dessa tecnologia, o desenvolvimento e as soluções dela. O objetivo é aj.
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California Institute of Technology Udemy

Generative AI for Beginners

Generative AI for Beginners Provider: Udemy Categories: Generative AI Courses, ChatGPT Courses, Prompt Engineering Courses, AI Ethics Courses Generative AI Made Easy: Embark on your journey with Generative AI. Learn the fundamentals of ChatGPT, Large Language Models (LLM), and prompt engineering. Gain hands-on experience by creating your own.
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California Institute of Technology Southern New Hampshire University

OpenAI GPTs: Creating Your Own Custom AI Assistants

OpenAI GPTs: Creating Your Own Custom AI Assistants In the era of Generative AI, the demand for personalized and specialized Generative AI assistants is skyrocketing. Large language models like GPTs have demonstrated their remarkable capabilities, but what if you could harness their power to create custom AI assistants tailored to your specific.
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California Institute of Technology Southern New Hampshire University

Generative AI for Legal Services Primer

Generative AI for Legal Services Primer Discover the transformative potential of Generative AI within the legal sector through this comprehensive course offered by Southern New Hampshire University on Coursera. Understand the fundamentals of Generative AI and its wide-ranging applications in legal tasks. The curriculum includes a deep dive into.
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California Institute of Technology University of Michigan

Leveraging Generative AI for Social Impact Organizations

Leveraging Generative AI for Social Impact Organizations Leveraging Generative AI for Social Impact Organizations focuses on addressing the issue of resource scarcity commonly faced by social impact organizations and highlights how generative AI tools can help free up limited staff capacity from routine administrative tasks. Social impact organi.
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California Institute of Technology University of Naples Federico II

Foundations of Local Large Language models

Course Title: Foundations of Local Large Language Models Description: By the end of this course, learners will have a solid understanding of Large Language Models running locally. You'll be able to set up a local environment using powerful tools to run different LLMs and interact with them both with a web interface as well as APIs. You will expl.
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California Institute of Technology Southern New Hampshire University

Generative AI Assistants

Generative AI Assistants Step into the frontier of digital assistance with the "Generative AI Assistants" specialization, your guide to crafting bespoke AI partners for any sector or specialized need. This course unveils the complexities of tailoring GPT-style language models that intuitively align with your world—be it legal, logistical, or scie.
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California Institute of Technology University of Naples Federico II

GenAI Basics - How LLMs Work

GenAI Basics - How LLMs Work Course: GenAI Basics - How LLMs Work Description: This one-hour course is designed for nontechnical audiences to grasp how GenAI models are trained. You will learn the basics of the data science process through an interactive demo that requires no software installation or downloads. University: University of Naples.
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California Institute of Technology Southern New Hampshire University

Prompt Engineering for Law

Prompt Engineering for Law Step into the cutting-edge intersection of law and technology with the "Prompt Engineering for Law" specialization, designed for legal professionals seeking to harness the power of Generative AI. This course introduces the foundations of Generative AI, exploring its burgeoning role in legal applications from contract a.
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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!