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Generative AI courses

1093 Courses

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California Institute of Technology Udemy

Generative AI for QA Professionals and Software Testers

Discover the power of Generative AI with our comprehensive course tailored for QA professionals and software testers. Offered by Udemy, this course provides hands-on experience in generating manual test cases and automating Selenium scripts seamlessly using cutting-edge AI technology right on your local system. Expand your expertise by divin.
provider Udemy
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California Institute of Technology Udemy

The Analytics Translator - Data Science Career Development

Unleash the full potential of your data science career by diving into the world of analytics translators. This course, provided by Udemy, offers valuable insights into this pivotal role that bridges the gap between data science teams and business stakeholders. Gain expertise in interpreting complex data insights and facilitating informed deci.
provider Udemy
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California Institute of Technology Coursera

Oracle Cloud Infrastructure Generative AI Professional

Enhance your expertise in cloud-based artificial intelligence by enrolling in the Oracle Cloud Infrastructure Generative AI Professional course. This course is designed to provide you with a deep understanding of Large Language Models (LLMs) and guide you through mastering the OCI Generative AI Service. You will also learn to build an innovat.
provider Coursera
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California Institute of Technology Southern New Hampshire University

Agentic AI and AI Agents: A Primer for Leaders

Discover the power of Agentic AI at Southern New Hampshire University, offered through Coursera. This innovative course is a must for leaders who want to stay competitive in the fast-paced world of AI-enhanced work. Agentic AI goes beyond traditional AI by acting on analyzed data, transforming industries by automating repetitive workflows a.
provider Coursera
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California Institute of Technology Coursera

Oracle Cloud Infrastructure AI Foundations

Join the Oracle Cloud Infrastructure AI Foundations course and dive into the world of AI. This course offers an in-depth introduction to key concepts in Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI. Specifically designed for those new to the field, it emphasizes practical applications of these technologies withi.
provider Coursera
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California Institute of Technology AWS Skill Builder

Lab - Explore Generative AI Use Cases with LangChain and Amazon Bedrock

Join the lab on exploring generative AI use cases with LangChain and Amazon Bedrock. This hands-on experience walks you through Jupyter notebooks where you will make API calls to generative AI models hosted on Amazon Bedrock. Your journey involves generating and summarizing text, answering questions, and building a chatbot using these powerful tool.
provider AWS Skill Builder
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California Institute of Technology Coursera

GenAI for Financial Data Analysis

Dive into the world of Generative AI (GEN AI) and its remarkable impact on financial data analysis. This course offers hands-on exploration into how AI tools such as Microsoft Co-Pilot, ChatGPT, Datarobot, and Chartpixel are revolutionizing financial analytics. Designed for those with a foundational understanding of financial data and AI, t.
provider Coursera
California Institute of Technology IGNOU

Generative AI for Everyday Life

Immerse yourself in the transformative power of Generative AI with our comprehensive 12-week course, "Generative AI for Everyday Life." Designed to cater to all, from students to professionals and educators, this course demystifies AI and showcases its impact on our daily activities. Kick off your journey by understanding the fundamentals of.
provider Swayam
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California Institute of Technology AWS Skill Builder

Lab - Exploring the Generative Business Intelligence Features in Amazon QuickSight

In this hands-on lab, you will step into the role of an Analyst at AnyCompany Banking & Financial company. The focus is on leveraging Amazon QuickSight’s Generative Business Intelligence (BI) features, such as QuickSight datasets, analysis, and QuickSight Q. You'll learn to analyze loan portfolio data and develop a robust dashboard delivering criti.
provider AWS Skill Builder
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California Institute of Technology XuetangX

科技赋能与数字化育人新范式-人工智能-GPT时代如何培养创新拔尖人才

provider XuetangX

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!