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Generative AI courses

1062 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 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 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

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 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

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 Coursera

Microsoft Copilot for Excel: AI-Powered Data Analysis

This course provides a practical, project-oriented learning experience with Microsoft Copilot in Excel, allowing you to tackle real-world data analytics challenges. Begin by exploring the basics of Microsoft Copilot, including its capabilities and limitations, while comparing it to generative AI tools like ChatGPT. Learn how to set up Copilot.
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California Institute of Technology Udemy

Intro to Generative AI for Business Professionals

Udemy Delve into the world of Generative AI with our comprehensive course specifically tailored for business professionals. Learn how to harness AI technologies to drive innovation and streamline your business operations. This practical guide covers essential AI concepts and tools, including: Generative Adversarial Networks (GAN) Variat.
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California Institute of Technology Udemy

Create docs & how-to guides using Generative AI with Guidde

Unlock the power of Generative AI to effortlessly craft expert documentation and how-to guides. Join our Udemy course aimed at empowering Product Owners and Product Managers to produce training materials, standard operating procedures (SOPs), and comprehensive guides with ease. Whether you're looking to enhance your technical writing skills o.
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California Institute of Technology Udemy

A CEO's Generative AI Playbook

Discover the essential playbook for CEOs looking to integrate Generative AI into their business strategy. Offered by Udemy, this course offers a comprehensive guide to mastering the use of AI in a strategic context. You'll learn about Generative AI, Retrieval Augmented Generation (RAG), AI agents, and the integration of these advanced technolog.
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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!