Generative AI courses

1093 Courses

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Generative AI SQL Database Specialist with ChatGPT

Discover the revolutionary integration of Generative AI and SQL databases to redefine how organizations craft, query, and visualize data systems. This pioneering specialization empowers you with cutting-edge skills necessary to lead database innovation at the intersection of SQL and AI, generating capabilities previously thought unattainable.
provider Coursera
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Generative AI For Business Leaders

Unlock the potential of Generative AI tailored for business leaders! This course is designed for individuals who do not have a background in analytics or data, offering a comprehensive introduction to the technology. You'll acquire essential knowledge on how Generative AI works and how to leverage it to achieve your business goals. By the conc.
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AI Training for Product Professionals

Join our comprehensive AI Training designed exclusively for product professionals. This course equips you with essential skills to streamline workflows and optimize your product decision-making process through the latest advancements in generative AI and prompt engineering. Explore a range of topics including: Artificial Intelligence Courses.
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Advanced AI Techniques for Product Marketing

Elevate your marketing strategy from data exploration through to launching campaigns with our comprehensive course on advanced AI techniques. This course is specially designed to equip product marketers with the latest generative AI practices and prompt engineering methods. Whether you're navigating through data analysis or gearing up for campai.
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Generative AI for NLP

Unlock the power of Generative AI for Natural Language Processing with our comprehensive course. Designed to be hands-on and self-paced, it offers the convenience of learning on your own schedule with the added benefit of live expert support. Whether you're looking to enhance your ability to extract valuable insights, automate various process.
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Generative AI: A Game Changer for Program Managers

Generative AI (GenAI) is revolutionizing the field of program management, allowing managers to make informed decisions, mitigate risks, and add strategic value more efficiently. This course offers professionals the opportunity to acquire job-ready skills in GenAI, making them more appealing to recruiters. Throughout the course, you'll discove.
provider Coursera
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AI for Professionals: Ethics, Responsibility and Best Practices

GenAI is pioneering innovative ways to enhance creativity and efficiency in our lives and workspaces. However, this technological advancement brings forth ethical dilemmas, such as AI bias, inaccuracy, and plagiarism, which fuel skepticism about its potential benefits. This course empowers learners with the expertise to manage and navigate these.
provider edX
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[RETIRING] Exam Prep Standard Course: AWS Certified AI Practitioner (AIF-C01)

This course offers a complete preparation path for the AWS Certified AI Practitioner (AIF-C01) exam. It is tailored for individuals who have up to 6 months of experience with AI and ML technologies on AWS and are familiar with these tools, even if they do not build solutions themselves. In the course, participants will: Gain a thorough und.
provider AWS Skill Builder
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Quiz - Generative AI Fundamentals

This course, developed by the AWS Training & Certification team in India, is designed to supplement the standard curriculum and enhance your AWS learning experience. As artificial intelligence rapidly transforms the digital world, understanding the basics of generative AI is crucial for professionals in every field. This quiz evaluates your grasp o.
provider AWS Skill Builder

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!