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Generative AI courses

1093 Courses

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California Institute of Technology Udemy

Complete guide for ACX for Research & Development

Unlock the full potential of ACX in the realm of research and development with this in-depth course. Whether your interests lie in data generation or prototyping, this comprehensive guide provides the knowledge and tools you need to succeed. Offered on Udemy, this course is perfect for anyone looking to expand their skills in artificial intell.
provider Udemy
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California Institute of Technology Tecnológico de Monterrey

Inteligencia Artificial Generativa para Docentes

Transforma tu enseñanza con IA Generativa y mejora tus habilidades pedagógicas. Este curso está especialmente diseñado para docentes, formadores y profesionales de la educación que desean integrar inteligencia artificial en su práctica educativa. A través de este innovador programa, aprenderás a utilizar herramientas de IA generativa para opti.
provider Coursera
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California Institute of Technology Udemy

Practical GenAI: Basics, Tools, Use cases, Ethics, Future

Welcome to Practical GenAI, a comprehensive guide perfect for new business employees looking to excel in the evolving world of AI technologies. This Udemy course covers the basics, tools, use cases, ethical considerations, and future prospects of AI in various business domains. Key Learning Areas: Automation: Discover how AI can streamline an.
provider Udemy
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California Institute of Technology Udemy

Prompt Engineering PRO (ChatGPT & Generative AI FAST-TRACK)

Elevate your skills with our Prompt Engineering PRO course, designed for fast-tracking expertise in ChatGPT and Generative AI. Learn effective tactics, enhance your content creation, and improve customer support strategies. As a bonus, this course includes a free AI Prompt Tool to maximize your learning potential. Perfect for those looking to.
provider Udemy
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California Institute of Technology Udemy

Hands-on SAP Build Code,JOULE AI, Low Code No Code,CAPM,HANA

Join our comprehensive course on Udemy to delve into SAP Build Code, exploring the Cloud Application Programming Model and the exciting realm of Generative Artificial Intelligence. This hands-on course is tailored for individuals eager to develop expertise in Low Code No Code methodologies, JOULE, and HANA integration. Perfect for tech enthusi.
provider Udemy
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California Institute of Technology Udemy

Adobe Firefly Mastery Course - Crafting Magic with Firefly

provider Udemy
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California Institute of Technology edX

Mastering Generative AI for Data Engineering

Generative AI skills are highly sought after. A report by Ascend.io indicates that 89% of professionals utilize generative AI in some aspect of their work. According to ZipRecruiter, data engineers with these skills can earn an average salary of USD 115,000, reaching up to USD 179,000 annually. This course is crafted for current and aspiring dat.
provider edX
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California Institute of Technology edX

Mastering Generative AI for Data Science

Mastering Generative AI for Data Science Generative AI is revolutionizing the data science field, and mastering its applications is vital for data science professionals. This comprehensive course offers advanced generative AI skills tailored specifically for data scientists. Dive into real-world scenarios where you will harness the power of genera.
provider edX
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California Institute of Technology edX

Generative AI and its Applications in Finance

Generative AI and its Applications in Finance Generative AI (GAI) is a powerful technology that enables computers to create new content, such as text, images, or financial data, by learning from existing patterns. Unlike traditional AI, which analyses and processes data, GAI leverages advanced machine learning models to generate realistic outputs.
provider edX
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California Institute of Technology edX

Mastering Generative AI for Data Analytics

Presently, 82% of global companies are embracing AI within their operations, marking generative AI skills as crucial for career advancement. Stay ahead by leveraging the power of generative AI in data analytics. This course, tailored for both budding and veteran data analysts, demands a basic understanding of data analytics, prompt engineering, P.
provider edX

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!