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Generative AI courses

542 Courses

California Institute of Technology Coursera

Gen AI for developers: Web development with Python & Copilot

Gen AI for Developers: Web Development with Python & Copilot This Guided Project, "Gen AI for Developers: Web Development with Python & CoPilot", is tailored for developers aiming to incorporate Copilot into their daily workflow. In this 1-hour, project-based course, you will learn to set up Copilot in VS Code, utilize it for learning new APIs,.
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provider Coursera
pricing Paid Course
duration 1-2 hours
sessions On-Demand
California Institute of Technology Coursera

Responsible AI: Applying AI Principles with GC - Español

Responsible AI: Applying AI Principles with GC - Español A medida que aumenta el uso empresarial de la inteligencia artificial y el aprendizaje automático, también crece la importancia de implementarlo responsablemente. El desafío para muchas personas es que hablar sobre la IA responsable puede ser más fácil que aplicarla. Si te interesa apren.
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provider Coursera
pricing Free Online Course (Audit)
duration 1-2 hours
sessions On-Demand
California Institute of Technology AWS Skill Builder

Planificación de un proyecto de IA Generativa (Español LATAM) | Planning a Generative AI Project (LATAM Spanish)

Planificación de un proyecto de IA Generativa es el segundo curso de una serie de tres partes llamada Fundamentos de la IA generativa para los responsables de decisiones técnicas y comerciales. Si aún no lo completó, comience con el primer curso de la serie, Introducción a la IA generativa - El Arte de lo posible. En este curso, aprenderá sobre.
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provider AWS Skill Builder
pricing Free Certificate
duration 1 hour
sessions On-Demand
California Institute of Technology Coursera

Gen AI for Software Development: Code Generation for Python

Gen AI for Software Development: Code Generation for Python Think coding is out of reach? With some help from generative AI, we can now easily break down problems and develop software to solve them. In this 1.5 hour guided project, we will break down the game logic for the game Hangman and then let generative AI help us produce.
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provider Coursera
pricing Paid Course
duration 2-3 hours
sessions On-Demand
California Institute of Technology Coursera

Building a Generative AI-Ready Organization

Building a Generative AI-Ready Organization Course | Coursera Building a Generative AI-Ready Organization The Building a Generative AI-Ready Organization course offers essential components required for the successful adoption of Generative AI within your organization. Tailored specifically for business leaders and key decision-makers.
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provider Coursera
pricing Free Online Course (Audit)
duration 1-2 hours
sessions On-Demand
California Institute of Technology Coursera

Amazon CodeWhisperer - Getting Started with Generative AI

Amazon CodeWhisperer - Getting Started with Generative AI Amazon CodeWhisperer is an artificial intelligence (AI) coding companion that can generate code suggestions in real time based on your comments and existing code. CodeWhisperer, which works in a variety of Integrated Development Environments (IDE), helps you reduce the time it takes to co.
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provider Coursera
pricing Free Online Course (Audit)
duration 1-2 hours
sessions On-Demand
California Institute of Technology

Amazon Bedrock - Getting Started with Generative AI

Amazon Bedrock - Getting Started with Generative AI Amazon Bedrock is a fully managed service that provides access to foundation models (FMs) from Amazon and top AI startups via an API. In this comprehensive course, you will discover the numerous benefits of Amazon Bedrock and learn how to get started with the service through a step-by-step demo.
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California Institute of Technology France Université Numerique

ChatGPT et IA : mode d'emploi pour managers et RH

ChatGPT et IA : mode d'emploi pour managers et RH Voici un mini MOOC pour comprendre la puissance des IA génératives comme ChatGPT, Bard, DALL-E, Midjourney, SlidesAI, et de l’ IA dans la transformation des métiers. Vous aurez des contenus uniques qui mettent en perspective la différence entre IA et IA génératives, les nouvelles questions q.
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provider France Université Numerique
pricing Free Online Course
duration 3 hours
sessions On-Demand
California Institute of Technology Coursera

Gen AI for Fraud Detection Analytics

Welcome to the 'Unlocking the Power of Generative AI in Fraud Detection Analytics' course, where you'll embark on a transformative journey to acquire practical expertise in generative AI for fraud prevention. Throughout this course, you'll delve into the world of AI-driven fraud detection, mastering the fundamentals and exploring real-world appl.
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provider Coursera
pricing Free Online Course (Audit)
duration 2-3 hours
sessions On-Demand
California Institute of Technology Coursera

Generative AI: Elevate Your Data Science Career

Generative AI: Elevate Your Data Science Career - Coursera Generative AI: Elevate Your Data Science Career Generative AI is now mainstream. Boost your career with a course that features leading-edge, in-demand generative AI skills tuned to the needs of data scientists. This course is suitable for existing and aspiring data.
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provider Coursera
pricing Free Online Course (Audit)
duration 11 hours
sessions On-Demand

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!