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Generative AI courses

1093 Courses

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California Institute of Technology Coursera

Gemini for Cloud Architects - Deutsch

Gemini für Cloud-Architekten - Deutsch | Coursera In diesem Kurs erfahren Sie, wie Gemini, ein auf generativer KI basierendes Produkt von Google Cloud, Administratoren bei der Bereitstellung von Infrastruktur unterstützt. Sie lernen die Prompts kennen, mit denen Gemini Infrastruktur erklären, GKE-Cluster bereitstell.
provider Coursera
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California Institute of Technology Coursera

Gemini for Cloud Architects - 日本語版

Gemini for Cloud Architects - 日本語版 University:   Provider:   Coursera Categories:   Generative AI Courses, Google Cloud Platform (GCP) Courses, Cloud Architecture Courses, Infrastructure Provisioning Courses このコースでは、Google Cloud の生成 AI を活用したコラボレーターである Gemini が、管理者によるインフラストラクチャ.
provider Coursera
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California Institute of Technology Coursera

Introduction to Large Language Models - 日本語版

Introduction to Large Language Models - 日本語版 このマイクロラーニングコースでは、大規模言語モデル（LLM）とは何か、どのようなユースケースで活用できるのか、プロンプト調整でLLMのパフォーマンスを高めるにはどうすればよいかについて学習します。ジェネレーティブAIアプリを自分で作成するのに役立つGoogleツールについても紹介します。 提供元: Coursera カテゴ.
provider Coursera
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California Institute of Technology Coursera

Introduction to Generative AI - 简体中文

Introduction to Generative AI - 简体中文 这是一节入门级微课程，旨在解释什么是生成式 AI、它的用途以及与传统机器学习方法的区别。该课程还介绍了可以帮助您开发自己的生成式 AI 应用的各种 Google 工具。 提供者: Coursera 类别: 机器学习课程, 生成式 AI 课程, 应用开发课程
provider Coursera
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California Institute of Technology Coursera

Gemini in Google Sheets - 繁體中文

安裝 Gemini 版 Google Workspace 外掛程式後，客戶就能在 Google Workspace 使用生成式 AI 功能。這堂迷你課程會介紹 Gemini 的主要功能，並說明如何在 Google 試算表善用這些功能，提高生產力和效率。 University: Provider: Coursera Categories: Generative AI Courses, Google Workspace Courses, Google Sheets Courses, Gemini Courses
provider Coursera
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California Institute of Technology Coursera

Gemini in Google Slides - 한국어

Google Workspace를 위한 Gemini는 고객에게 Google Workspace의 생성형 AI 기능을 제공하는 부가기능입니다. 이 미니 학습 과정에서는 Gemini의 주요 기능을 살펴보고 이러한 기능으로 Google Slides의 생산성과 효율성을 향상하는 방법을 알아봅니다. University: Provider: Coursera Categories: Generative AI Courses Google Workspace Courses Goo.
provider Coursera
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California Institute of Technology Coursera

Gemini in Google Sheets - 日本語版

Gemini in Google Sheets - 日本語版 Title: Gemini in Google Sheets - 日本語版 Description: Gemini for Google Workspace は、Google Workspace の生成 AI 機能をお客様に提供するアドオンです。このミニコースでは、Gemini の主な機能と、それらの機能を使用して Google スプレッドシートの生産性と効率を向上させる方法について学びます。 University: Provider: Cour.
provider Coursera
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California Institute of Technology Coursera

Gemini in Google Sheets - 简体中文

Gemini in Google Sheets - 简体中文 University: Provider: Coursera Categories: Generative AI Courses, Google Sheets Courses, Gemini Courses
provider Coursera
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California Institute of Technology Coursera

Gemini in Gmail - 한국어

Gemini in Gmail - 한국어 Google Workspace를 위한 Gemini는 고객에게 Google Workspace의 생성형 AI 기능을 제공하는 부가기능입니다. 이 미니 학습 과정에서는 Gemini의 주요 기능을 살펴보고 이러한 기능으로 Gmail의 생산성과 효율성을 향상하는 방법을 알아봅니다. University: Provider: Coursera Categories: Generative AI Courses, Productivity Courses, Google.
provider Coursera
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California Institute of Technology Coursera

Gemini in Google Docs 繁體中文

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!