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Generative AI courses

1093 Courses

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California Institute of Technology Udemy

The Complete Generative AI and Python Programming Bootcamp

Master New Skills for Your Future: Python, Generative AI, LangChain, LangGraph, RAG, Prompt Engineering, OpenAI + Gemini
provider Udemy
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California Institute of Technology edX

Azure AI Fundamentals: Build & Deploy AI

This course offers a comprehensive introduction to artificial intelligence (AI) concepts and the array of Azure services available for developing AI solutions. Designed for individuals with both technical and non-technical backgrounds, this course requires no prior experience in data science or software engineering. It is ideal for professionals l.
provider edX
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California Institute of Technology Google Cloud Skills Boost

Gen AI: Unlock Foundational Concepts

Gen AI: Unlock Foundational Concepts is the second course of the Gen AI Leader learning path. In this course, you unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI, and understanding how various data types enable generative AI to address business challenges. You also gain insights into Google.
provider Google Cloud Skills Boost
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California Institute of Technology Google Cloud Skills Boost

Gen AI: Navigate the Landscape

Gen AI: Navigate the Landscape is the third course of the Gen AI Leader learning path. Gen AI is changing how we work and interact with the world around us. But as a leader, how can you harness its power to drive real business outcomes? In this course, you explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the.
provider Google Cloud Skills Boost
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California Institute of Technology Google Cloud Skills Boost

Gen AI: Beyond the Chatbot

Gen AI: Beyond the Chatbot is the first course of the Gen AI Leader learning path and has no prerequisites. This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization. You explore concepts like foundation models and prompt engineering, which are crucial for leveraging the.
provider Google Cloud Skills Boost
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California Institute of Technology Google Cloud Skills Boost

Gen AI Apps: Transform Your Work

Transform Your Work With Gen AI Apps is the fourth course of the Gen AI Leader learning path. This course introduces Google's gen AI applications, such as Gemini for Workspace and NotebookLM. It guides you through concepts like grounding, retrieval augmented generation, constructing effective prompts and building automated workflows.
provider Google Cloud Skills Boost
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California Institute of Technology Google Cloud Skills Boost

Gen AI Agents: Transform Your Organization

Gen AI Agents: Transform Your Organization is the fifth and final course of the Gen AI Leader learning path. This course explores how organizations can use custom gen AI agents to help tackle specific business challenges. You gain hands-on practice building a basic gen AI agent, while exploring the components of these agents, such as models, reason.
provider Google Cloud Skills Boost
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California Institute of Technology Coursera

AWS Certified AI Practitioner

Welcome to the transformative journey that is the AWS Certified AI Practitioner Course! In today's rapidly changing AI landscape, having a firm grasp of AI concepts is critical, but knowing how to implement these concepts on AWS is where the challenge—and opportunity—lies. If you've ever felt overwhelmed by the complexities of integrating AI into A.
provider Coursera
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California Institute of Technology AWS Skill Builder

Quiz - Generative AI Fundamentals

This course was developed by members of AWS Training & Certification India. The content is intended to complement our standard training curriculum and augment your AWS learning journey. As artificial intelligence continues to reshape our digital landscape, understanding the basics of generative AI has become essential for professionals across all.
provider AWS Skill Builder
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California Institute of Technology Southern New Hampshire University

Generative AI Database Design & Management with ChatGPT

Imagine designing databases that evolve with your business, anticipate future needs, and solve problems you haven't even encountered yet. This course teaches you to use AI as your intelligent design partner—creating database architectures neither human nor AI could achieve alone. You'll master AI-powered design techniques that transform traditional.
provider Coursera

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!