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Generative AI courses

911 Courses

California Institute of Technology Coursera

Job Search with GenAI

Embark on a transformative journey through the job search process with our comprehensive course on Job Search with GenAI. Leveraging the power of generative AI, this course provides you with the practical skills and innovative tools essential for modern job hunting. Whether you're starting your career or searching for your next opportunity,.
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California Institute of Technology Coursera

GenAI for Legal Research

In today's dynamic legal landscape, efficiently handling large volumes of information is vital. This course on Generative AI is crafted to enhance your legal practice by streamlining research, refining document drafting, and forecasting case outcomes. Discover AI's potential to transform workflows while upholding ethical standards and gaining.
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California Institute of Technology Coursera

ChatGPT & Generative AI for Data Analytics

Join the course "ChatGPT & Generative AI for Data Analytics" to explore advanced tools that enhance your ability to work smarter and faster as a data professional. Dive into deep learning and generative AI, and understand the rapid development of large language models like ChatGPT and Gemini. Access free resources to enhance your skills and boo.
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California Institute of Technology Coursera

GenAI for Personalized Marketing at Scale

Join the comprehensive course on "GenAI for Personalized Marketing at Scale" to elevate your marketing strategies using advanced Generative AI technologies. Learn how to create customized content tailored for various customer segments across multiple platforms, including social media and websites. This course suits marketing professionals,.
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California Institute of Technology Coursera

GenAI for Financial Forecasting and Planning

Join our course designed to empower financial professionals with the transformative capabilities of Generative AI in forecasting and planning. Discover how AI-driven tools can streamline processes, enhance accuracy, and optimize strategic decision-making. By completing this course, you'll be able to automate financial predictions and validate.
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California Institute of Technology Udemy

Hallucination Management for Generative AI

Unlock the secrets to effectively managing hallucinations in language learning models (LLMs) and generative AI with this comprehensive course on Udemy. Delve into scientifically backed strategies that equip you with the necessary skills to handle and mitigate hallucinations. This course is perfect for anyone looking to enhance their understan.
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California Institute of Technology Udemy

Microsoft Copilot World (Microsoft 365, MS Purview) 25+ Hour

Join an engaging and comprehensive course on Udemy, where you'll dive deep into the world of Microsoft Copilot. With over 25 hours of content, this course provides a robust understanding of Microsoft technologies, including Microsoft 365, Microsoft Purview with a focus on securing generative AI, and explore tools like Azure Portal Copilot and.
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California Institute of Technology Udemy

Get AWS AI Certified: HandsOn,Quiz & Tests|Zero-to-Hero 2025

Get AWS AI Certified: Hands-On, Quiz & Tests | Zero-to-Hero 2025 Join our expertly designed course for a comprehensive preparation to achieve your AWS AI Certification. Benefit from hands-on experience through curated practice tests in collaboration with the Amazon Team. Fast-track your path to certification and aim to succeed in your first at.
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California Institute of Technology Coursera

GenAI for Sales Analytics

Explore the innovative intersection of Generative AI and sales analytics with our specialized course. Tailored for those eager to enhance their AI skills, this program covers the transformative role of AI in sales, focusing on improving forecasting precision, customer segmentation, and strategic refinement. Participants will delve into.
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California Institute of Technology Southern New Hampshire University

Generative AI Cybersecurity & Privacy for Leaders: A Primer

Are you prepared to steer your organization into the future of cybersecurity, prioritizing privacy in an increasingly AI-centric environment? This primer provides a foundational understanding of generative AI, exploring its transformative possibilities alongside the cybersecurity and privacy risks it introduces. It empowers you to embrace AI’s.
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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!