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Generative AI courses

1093 Courses

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California Institute of Technology AWS Skill Builder

Generative BI with Amazon Q in Quicksight - Getting Started (Traditional Chinese)

Amazon Q in QuickSight integrates Amazon Bedrock's large language models (LLM) with Amazon QuickSight's AI features, introducing new Business Intelligence (BI) capabilities. In this course, you will learn the technical concepts and advantages of using Amazon Q in QuickSight. You will discover the architecture of Amazon Q in QuickSight and how.
provider AWS Skill Builder
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California Institute of Technology Southern New Hampshire University

From Data to Decisions: Getting Started with AI

Embark on your AI journey and transform your organizational data into actionable insights with Southern New Hampshire University's course, "From Data to Decisions: Getting Started with AI," available on Coursera. This course caters to individuals eager to work with organizational data but unsure where to begin. Leverage the power of generative A.
provider Coursera
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California Institute of Technology SAP Learning

Generative AI at SAP

Discover how artificial intelligence (AI) transforms business processes with the 'Generative AI at SAP' course. This program provides a comprehensive understanding of AI's fundamental uses and benefits in a professional setting. Participants will explore different AI methodologies and study detailed use cases. Upon completion, attendees will gain.
provider SAP Learning
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California Institute of Technology Coursera

Interactive and Immersive Experiences with Generative AI

Embark on a transformative journey with the "Interactive and Immersive Experiences with Generative AI" course, your gateway to leveraging AI in the realms of creative industries and interactive media. Delve into a curriculum that seamlessly blends theoretical insights with practical demonstrations to empower your creative collaborations and re.
provider Coursera
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California Institute of Technology AWS Skill Builder

Princípios da engenharia de prompts (Português) | Foundations of Prompt Engineering (Portuguese)

Neste curso, você aprenderá os princípios, as técnicas e as práticas recomendadas para criar prompts eficazes. Este curso apresenta os elementos básicos da engenharia de prompts e avança para técnicas avançadas de prompts. Você também aprenderá a se proteger contra o uso indevido de prompts e a mitigar a interação com FMs. Nível do curso: int.
provider AWS Skill Builder
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California Institute of Technology University of California, Davis

AI for Knowledge Workers

Enroll Now - Enhance your skills in AI with the University of California, Davis through Coursera. This beginner-friendly course is your gateway to understanding AI, from Machine Learning to Generative AI, enabling you to transform your approach to both creative and critical thinking tasks in the workplace. Learn to harness AI technologies like.
provider Coursera
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California Institute of Technology Microsoft Learn

Ethical AI

Ethical AI Enhance your understanding of ethical AI with Microsoft's comprehensive course. This program covers critical areas such as AI workloads and Azure AI Services, emphasizing Microsoft's commitment to Responsible AI policies. Module 1: Explore AI solutions and the essentials of responsible AI practices. Discover the potential.
provider Microsoft Learn
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California Institute of Technology AWS Skill Builder

AWS Flash - Chalk Talks: Generative AI on AWS (Japanese)

このコースでは、AWS で生成 AI アプリケーションを構築しようとしているお客様が利用できるさまざまなオプションについて解説します。このコースでは特に、Amazon SageMaker Jumpstart の基盤モデルを活用して生成 AI アプリケーションを構築する方法に焦点を当てます。 コースレベル: 基礎 所要時間: 55 分 このコースにはスライドとデモが含まれています。 このコ.
provider AWS Skill Builder
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California Institute of Technology AWS Skill Builder

AWS Flash - Chalk Talks: Generative AI on AWS (Korean)

이 과정에서는 고객이 AWS에서 생성형 AI 애플리케이션을 빌드할 때 사용할 수 있는 옵션을 간략하게 설명합니다. 이 과정은 특히 Amazon SageMaker JumpStart의 파운데이션 모델을 활용하여 생성형 AI 애플리케이션 빌드를 중점적으로 설명합니다. 과정 수준: 기초 소요 시간: 55분 참고: 이 과정의 동영상에는 한국어 트랜스크립트 또는 자막이 지원되며 음성은.
provider AWS Skill Builder
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California Institute of Technology University of Michigan

Navigating Disruption: Generative AI in the Workplace

Generative AI is set to become one of the most transformative technologies of our time. Join the course series "Navigating Disruption: Generative AI in the Workplace" to gain a clear understanding of how this technology functions, learn from historical tech disruptions, and discover the potential roles AI might assume in future workplaces. O.
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!