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Generative AI courses

1062 Courses

California Institute of Technology Coursera

Maximizing the Generative AI Value

Generative AI is transforming industries by automating creativity, optimizing processes, and fostering growth. This course, "Maximizing the Generative AI Value," empowers learners to leverage AI for innovative solutions and increased operational efficiency across various sectors. Studies show AI assists over 60% of daily tasks, enhancing outcom.
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California Institute of Technology Coursera

Generative AI for Executives and Business Leaders

Generative AI is reshaping industries, providing executives and business leaders with extraordinary opportunities to foster innovation and enhance business value. In this specialization by IBM, discover how to strategically harness this revolutionary technology and confidently integrate it into your organization. Engage in short courses le.
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California Institute of Technology AWS Skill Builder

AWS Flash - AWS Security: Securing Generative AI on AWS

This course is designed for Security and AI/ML technical users focusing on securing generative AI on AWS. Learn about the AWS Gen AI Security Scoping Matrix to effectively categorize and secure AI implementations. Explore the MITRE ATLAS framework and OWASP's Top 10 threats to Generative AI, along with comprehensive security strategies across go.
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California Institute of Technology Pluralsight

Can GenAI Help Future Proof Your Career?

Explore how generative AI can bolster your career in our engaging session with experts Tim Warner and Michael Teske. Delve into historical tech evolutions from personal computers in the 1970s to cloud computing in the 2000s, and see how today's AI trends mirror past innovations. Gain practical insights and strategies to leverage AI effective.
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California Institute of Technology Pluralsight

Generative AI for Innovators

Generative AI for Innovators - Pluralsight Generative AI tools have the power to transform product innovation dramatically. Enroll in this course to learn how to effectively utilize these tools in developing new products and solutions. Innovators frequently face challenges in making quick, informed decisions amidst the fast-pac.
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California Institute of Technology Pluralsight

Generative AI for Colleagues

Unlock the potential of generative AI with the "Generative AI for Colleagues" course offered by Pluralsight. This comprehensive course empowers you to transform meeting notes into efficient and actionable project documentation using advanced AI tools. Throughout the course, you will: Explore essential setups for meeting recording and sum.
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California Institute of Technology Pluralsight

Generative AI for Researchers

Generative AI tools that can access and search the internet offer a significant advantage for researchers. These tools can quickly analyze and synthesize information across various topics faster than traditional manual methods. Given the time-consuming nature of research, where vast amounts of information need sifting and analysis, generative AI.
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California Institute of Technology Pluralsight

Practical Strategies for AIOps Success

Join Tim Warner and a special guest in this insightful session as they delve into essential knowledge for IT professionals about AIOps. Critical topics include practical implementation tactics and harnessing generative AI for impactful transformation. Once considered futuristic, Artificial Intelligence for IT Operations (AIOps) is now revolut.
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California Institute of Technology AWS Skill Builder

Developing Generative Artificial Intelligence Solutions (Tiếng Việt)

Phát Triển Giải Pháp Trí Tuệ Nhân Tạo Tạo Sinh (Tiếng Việt) - AWS Skill Builder Trong khóa học này, bạn sẽ khám phá vòng đời của ứng dụng trí tuệ nhân tạo tạo sinh (AI tạo sinh), bao gồm: Xác định trường hợp sử dụng trong kinh doanh Chọn mô hình nền tảng (FM) Cải thiện hiệu suất của FM Đánh giá hiệu suất của FM Triển khai và tác động.
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California Institute of Technology AWS Skill Builder

Exploring Artificial Intelligence Use Cases and Applications (Tiếng Việt)

Trong khóa học này, bạn sẽ khám phá các trường hợp sử dụng trí tuệ nhân tạo (AI), máy học (ML) và trí tuệ nhân tạo tạo sinh (AI tạo sinh) trong thực tế ở nhiều ngành khác nhau. Các lĩnh vực này bao gồm y tế, tài chính, tiếp thị, giải trí, v.v. Bạn cũng sẽ tìm hiểu về khả năng và hạn chế của AI, ML và AI tạo sinh, các kỹ thuật lựa chọn mô hình và.
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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!