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Generative AI courses

659 Courses

California Institute of Technology Pluralsight

Security Risks and Privacy Concerns Using Generative AI

Generative AI has the profound ability to impact and influence cybersecurity, yielding both favorable and adverse consequences. This course will teach you foundational aspects of generative AI and its implications on data and privacy concerns and how to remediate them. In today’s current cyber landscape, threats are constantly evolving, and i.
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provider Pluralsight
pricing Free Trial Available
duration 25 minutes
sessions On-Demand
California Institute of Technology Skillshare

ChatGPT: Increased Productivity for Creative Professionals

Welcome to "Generative AI for Creative Professionals"! As a creative professional, you may have heard about Generative AI and its potential to revolutionize the way we work. But what exactly is Generative AI, and how can it be used in creative work? In this class, we will explore the basics of Generative AI and its limitations. We will also dive i.
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provider Skillshare
pricing Free Trial Available
duration 29 minutes
sessions On-Demand
California Institute of Technology

Introduction to generative AI for trainers

Introduction to Generative AI for Trainers Module 1: By understanding the basics of generative AI models, you empower yourself to make responsible decisions when using these models. This knowledge allows you to critically evaluate outputs, assess their reliability, and understand potential limitations leading to more inf.
California Institute of Technology Udemy

Generative AI with Google - Bard, PaLM API and Gen AI Studio

Generative AI with Google - Bard, PaLM API and Gen AI Studio Begin your Generative AI journey today with comprehensive courses on Google Bard, PaLM API, and Google Cloud Generative AI Studio. Available now on Udemy. Categories: Generative AI Courses, Google Bard Courses
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provider Udemy
pricing Paid Course
duration 4 hours 49 minutes
sessions On-Demand
California Institute of Technology Coursera

GenAI for Everyone

GenAI for Everyone This course offers a foundational journey into the world of Generative AI (GenAI), setting the stage for a comprehensive learning path that delves into the nuanced, role-specific applications of AI. Designed to equip learners with essential GenAI knowledge, this primer is the perfect starting point before progress.
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California Institute of Technology Coursera

AI Infrastructure and Operations Fundamentals

AI Infrastructure and Operations Fundamentals Artificial Intelligence, or AI, is transforming society in many ways. From speech recognition to self-driving cars, to the immense possibilities offered by generative AI. AI technology provides enterprises with the compute power, tools, and algorithms their teams need to do t.
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California Institute of Technology University of Michigan

Responsible Generative AI

Responsible Generative AI - University of Michigan | Coursera Responsible Generative AI is a Specialization exploring the possibilities and risks of generative artificial intelligence (AI). You will establish a comprehensive understanding of the impact of this technology. The series will help you identify impacts relevant to business operations,.
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California Institute of Technology University of Michigan

Generative AI: Labor and the Future of Work

Join the course "Generative AI: Labor and the Future of Work" and gain a comprehensive understanding of how generative artificial intelligence (AI) is transforming jobs and everyday tasks. As generative AI continues to evolve, organizations are discovering novel ways to integrate these technologies, fundamentally reshaping the job landscape. P.
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California Institute of Technology Coursera

Generative AI for Data Visualization and Data Storytelling

Generative AI for Data Visualization and Data Storytelling In today’s data-driven world, harnessing the power of Generative AI to create impactful data visualizations is essential for effective communication and decision-making. This course focuses on utilizing cutting-edge AI tools to transform raw data into dynamic, insightful visual artifacts,.
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California Institute of Technology Coursera

Artificial Intelligence

Artificial Intelligence Designed as an introduction to the evolving area of AI, this course emphasizes potential business applications and related managerial insights. Artificial Intelligence (AI) is the science behind systems that can program themselves to classify, predict, and offer solutions based on structured and unstructured data. For mil.
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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!