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Generative AI courses

542 Courses

California Institute of Technology LinkedIn Learning

Become an AI-Powered Learning and Development Professional

Become an AI-Powered Learning and Development Professional This learning path delves into building AI aptitude in your organization, considering generative AI, responsible AI leadership, digital mindset cultivation, and real-world problem-solving. Led by experts, you'll leverage AI effectively while upholding ethical practices, ensuring you can.
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California Institute of Technology LinkedIn Learning

ChatGPT and Power BI

ChatGPT and Power BI Course - LinkedIn Learning Join our beginner-friendly course on LinkedIn Learning and discover how to leverage Power BI and ChatGPT together for enhanced efficiency and smarter, data-driven decisions. Perfect for those looking to expand their knowledge in: Artificial Intelligence Business Intelligence Generative AI C.
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California Institute of Technology AWS Skill Builder

Amazon Q Introduction (Vietnamese)

Amazon Q Introduction (Vietnamese) Khóa học này cung cấp thông tin tổng quan cấp độ cao về Amazon Q, một trợ lý dựa trên nền tảng trí tuệ nhân tạo (AI) tạo sinh. Bạn sẽ tìm hiểu về các trường hợp sử dụng và lợi ích của việc liên kết Amazon Q với thông tin, mã và hệ thống của công ty bạn. Bạn cũng sẽ tìm thấy thông tin bổ sung để thúc đẩy hành tr.
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California Institute of Technology LinkedIn Learning

Using AI for UX Design and Research

Using AI for UX Design and Research Explore the many ways in which UX designers and researchers can ethically and inclusively leverage AI in their workflows.
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California Institute of Technology LinkedIn Learning

Accessibility and AI: Bridging the Disability Divide

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California Institute of Technology AWS Skill Builder

Digital Classroom - Generative AI for Executives

Digital Classroom - Generative AI for Executives Generative AI for Executives will teach you how to leverage the power of generative AI to drive real business value. You'll start by recognizing the potential of these new AI technologies and identifying specific use cases you can implement right away. From there, you'll cover best practices for usi.
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California Institute of Technology LinkedIn Learning

Hands-On Generative AI with Multi-Agent LangChain: Building Real-World Applications

Hands-On Generative AI with Multi-Agent LangChain: Building Real-World Applications Learn how to build and run dynamic, interactive multiagent simulations using LangChain in this comprehensive course from LinkedIn Learning. This hands-on course will guide you through the exciting world of generative AI and demonstrate how to create real-world a.
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California Institute of Technology LinkedIn Learning

Building ChatGPT Skills for Marketing

Building ChatGPT Skills for Marketing Discover how AI is revolutionizing marketing. Whether you're a seasoned marketer or just starting out, gain the requisite skills to leverage AI for marketing success. Learn from industry experts as they share insights on AI applications, tools, and strategies. Develop a plan to integrate AI into your marke.
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California Institute of Technology LinkedIn Learning

Foundational AI Skills for Azure Administration

Foundational AI Skills for Azure Administration | LinkedIn Learning Build foundational Azure skills in generative AI and predictive AI. Grasp core concepts and explore generative AI cloud services and use cases. Gain hands-on experience with the Microsoft Azure ecosystem and develop essential skills for deploying AI solutions. Learn to apply eth.
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California Institute of Technology LinkedIn Learning

Using Gen AI to Develop Personalized Learning Plans

Using Gen AI to Develop Personalized Learning Plans Unlock the potential of generative AI in designing individualized educational plans. This course offered by LinkedIn Learning delves into how AI-driven technologies can create hyperpersonalized learning experiences. Perfect for educators and instructional desi.
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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!