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Generative AI courses

1062 Courses

California Institute of Technology AWS Skill Builder

Responsible Artificial Intelligence Practices (Tiếng Việt)

Trong khóa học này, bạn sẽ tìm hiểu về các phương pháp thực hành AI có trách nhiệm. Đầu tiên, bạn sẽ tìm hiểu định nghĩa về AI có trách nhiệm, những thách thức cần giải quyết và khám phá các phương diện cốt lõi. Sau đó, bạn sẽ tìm hiểu sâu về phát triển hệ thống AI với các dịch vụ và công cụ AWS. Khóa học cũng sẽ hướng dẫn cân nhắc lựa chọn mô.
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California Institute of Technology Microsoft Learn

AI Fluency

Module 1: Discover the history and foundational concepts of artificial intelligence. Learn how AI impacts daily life and evaluate AI, machine learning, and deep learning concepts, algorithms, and historical milestones. Module 2: Understand generative AI fundamentals and their effect on creativity and productivity. Distinguish between NL.
California Institute of Technology Coursera

GenAI for Performance Management

Unlock the potential of Generative AI in optimizing performance management with our course. Dive into how GenAI enhances goal setting, performance monitoring, and feedback, enabling a more efficient and personalized approach to employee growth and organizational alignment. Participants will learn to leverage GenAI for automation and coaching,.
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California Institute of Technology Coursera

Develop GenAI Apps with Gemini and Google Maps

Develop GenAI Apps with Gemini and Google Maps Enhance your skills by participating in a self-paced lab focused on creating and testing proof of concept code snippets for a Travel Agent application. This lab takes place within the Google Cloud console and leverages the powerful Gemini Pro model, Vertex AI Python SDK, and Google Maps API. Prov.
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California Institute of Technology Coursera

GenAI for Execs & Business Leaders: Integration Strategy

Are you an executive or business leader eager to strategically integrate AI into your organization? This concise course provides essential insights from IBM leaders on integrating GenAI at scale. Learn to drive ROI, leverage data for competitive advantage, and devise effective use cases, all while ensuring compliance and strong governance..
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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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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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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!