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Generative AI courses

847 Courses

California Institute of Technology AWS Skill Builder

Developing Generative Artificial Intelligence Solutions (ไทย)

ในหลักสูตรนี้ คุณจะสำรวจวงจรชีวิตของแอปพลิเคชันปัญญาประดิษฐ์ช่วยสร้าง (Generative AI หรือ AI ช่วยสร้าง) ได้แก่ การกำหนดกรณีใช้งานทางธุรกิจ การเลือกโมเดลพื้นฐาน (FM) การปรับปรุงประสิทธิภาพของ FM การประเมินประสิทธิภาพของ FM การนำไปใช้จริงและผลกระทบต่อวัตถุประสงค์ทางธุรกิจ หลักสูตรนี้เป็นการปูพื้นฐานไปสู่หลักสูตร AI ช่วยสร้างหลักสูตรต.
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California Institute of Technology Coursera

GenAI for Executives & Business Leaders: An Introduction

AI is impacting every facet of business and daily life. As Arthur C. Clarke noted, "Any sufficiently advanced technology is indistinguishable from magic." Yet, artificial intelligence (AI) is rooted in math and science, and its influence will pervade all aspects of existence. This course by IBM AI Academy seeks to enlighten executives about AI's.
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California Institute of Technology AWS Skill Builder

Exploring Artificial Intelligence Use Cases and Applications (ไทย)

ในหลักสูตรนี้ คุณจะได้ศึกษากรณีใช้งานในสถานการณ์จริงว่าด้วยการนำปัญญาประดิษฐ์ (AI), แมชชีนเลิร์นนิง (ML) และปัญญาประดิษฐ์ช่วยสร้าง (AI ช่วยสร้าง) ไปใช้ในอุตสาหกรรมต่างๆ อาทิ อุตสาหกรรมการดูแลสุขภาพ การเงิน การตลาด ความบันเทิง และอื่นๆ อีกมากมาย นอกจากนี้คุณยังจะได้เรียนรู้เกี่ยวกับความสามารถและข้อจำกัดของ AI, ML และ AI ช่วยสร้าง เทคนิคการเลื.
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California Institute of Technology Coursera

GenAI for Healthcare Ethics

Delve into the transformative potential of Generative AI in healthcare with our course on Healthcare Ethics. Gain essential skills to address ethical challenges, ensuring AI systems are fair, transparent, and prioritize the well-being of patients. Learn how to identify and mitigate bias in AI models while developing informed consent policies.
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California Institute of Technology Coursera

Improving Diagnostic Accuracy with GenAI

Join our comprehensive course designed for healthcare professionals, AI enthusiasts, and anyone interested in the fusion of technology and medicine. Learn to leverage the power of GenAI to enhance diagnostic accuracy through hands-on, practical applications. Discover how to integrate existing GenAI tools into diagnostic workflows without buil.
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California Institute of Technology Canvas Network

GenAI in Action: Impact and Possibilities

Explore the boundless potential of Artificial Intelligence with the comprehensive AI and ChatGPT course from the prestigious University of South Florida. This expertly designed course, offered through Canvas Network, delves deep into the realms of AI, machine learning, and generative AI. Whether you're interested in enhancing your knowledge of.
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California Institute of Technology AWS Skill Builder

Exploring Artificial Intelligence Use Cases and Applications (한국어)

이 과정에서는 다양한 산업의 실제 인공 지능, 기계 학습(ML) 및 생성형 인공 지능(생성형 AI) 사용 사례를 살펴봅니다. 이러한 산업에는 의료, 금융, 마케팅, 엔터테인먼트 등이 포함됩니다. 또한 AI, ML, 생성형 AI의 기능 및 제한 사항, 모델 선택 기법, 주요 비즈니스 지표에 대해서도 알아봅니다. 과정 수준: 기초 소요 시간: 1시간 이 과정에는 대화형 요소,.
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California Institute of Technology AWS Skill Builder

Developing Generative Artificial Intelligence Solutions (简体中文)

在本课程中，您将探索生成式人工智能应用程序生命周期，其中包括以下内容： 定义业务使用案例 选择基础模型 (FM) 提高 FM 的性能 评估 FM 的性能 部署及其对业务目标的影响 本课程是生成式人工智能课程的入门课程，这些课程深入探讨了使用提示工程、检索增强生成 (RAG) 和微调技术自定义 FM 的相关概念。 课程级别：基础级 时长：1 小时 注意：本课程具有.
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California Institute of Technology AWS Skill Builder

Responsible Artificial Intelligence Practices (한국어)

In this course, you will explore responsible AI practices. It begins with an introduction to what responsible AI means, including defining responsible AI, understanding the challenges it seeks to overcome, and exploring its core elements. Next, the course delves into various topics for developing responsible AI systems and introduces the services.
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California Institute of Technology Coursera

GenAI for Sales Proposals and Presentations

Experience a revolutionary approach to sales proposals and presentations with "GenAI for Sales Proposals and Presentations," a course offered by Coursera. Tailored for sales professionals, this course empowers you to harness generative AI to create personalized and visually striking sales materials efficiently. Imagine crafting data-driv.
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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!