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Generative AI courses

1014 Courses

California Institute of Technology Udemy

AI Fundamentals: Essential Guide to Artificial Intelligence

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California Institute of Technology Udemy

Mastering Generative AI: LLMs, Prompt Engineering & More!

Unlock the power of Generative AI with the "Mastering Generative AI: LLMs, Prompt Engineering & More!" course on Udemy. This complete guide is designed to equip you with the skills necessary to build and deploy state-of-the-art AI models. Dive deep into the world of Large Language Models (LLMs), learn the nuances of prompt engineering, and exp.
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California Institute of Technology Udemy

Introduction to AI and ChatGPT

Join our 'Introduction to AI and ChatGPT' course offered by Udemy to explore the exciting realm of Artificial Intelligence. This course covers a wide range of topics including Dell-E, Generative AI, Machine Learning, and Deep Learning. Get ahead in your career by developing skills in AI, gaining proficiency in ChatGPT, and prompt engineering.
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California Institute of Technology Udemy

Mastering AWS Certified AI Practitioner AIF-C01 - Hands On!

Enroll Now Discover the path to AWS AIF-C01 Certification with Udemy's comprehensive prep course. Engage in hands-on practice tests, explore AI fundamentals, and learn how to utilize powerful tools such as Bedrock and SageMaker. Ideal for enthusiasts in Artificial Intelligence, this course also covers Machine Learning, Generative AI, MLOps, an.
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California Institute of Technology Udemy

Dominate SEO with ChatGPT: The AI Powered Search Revolution

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California Institute of Technology Udemy

AI-900 Azure AI Fundamentals: Crash Course

Embark on the journey of mastering Microsoft Azure AI Services with our AI-900 Azure AI Fundamentals: Crash Course. Designed to help you ace the AI-900 certification exam, this course provides in-depth knowledge of Azure’s AI capabilities, opening the door to opportunities in the fields of Artificial Intelligence, Machine Learning, and Cloud.
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California Institute of Technology Udemy

Create Stunning Images and Videos with Midjourney & AI Tools

Discover the power of AI in art creation with our course, "Create Stunning Images and Videos with Midjourney & AI Tools." This Udemy offering will guide you through the process of crafting unique pieces of art and turning them into captivating videos using the latest in Artificial Intelligence technology. Whether you are an aspiring artist, a.
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California Institute of Technology Udemy

ChatGPT Mega Course: Midjourney, Adobe Firefly AI, ChatGPT 4

Explore the ChatGPT Mega Course offered by Udemy, featuring over 25 cutting-edge AI tools including ChatGPT 4, GPT plugins, and ChatGPT API. Dive into the realms of Midjourney, Generative AI, and Adobe Firefly, and enhance your skills in Prompt Engineering. This comprehensive course spans various categories such as Artificial Intelligence, Gener.
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California Institute of Technology Udemy

Generative AI:Beginner to Pro with OpenAI & Azure OpenAI

Advance from beginner to pro in Generative AI with our comprehensive course featuring Gen-AI Basics, OpenAI, and Azure OpenAI. Learn everything from AI Search and RAG to Fine Tuning, Assistants API, and more. Hone your skills with ChatGPT, Code Interpreter, Function Calling, and File Search through this expertly designed course offered by Ude.
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California Institute of Technology Udemy

Copilot Microsoft 365 (Copilot AI + Excel, Word, PowerPoint)

Unlock the potential of artificial intelligence in your daily tasks with our specialized course: Copilot Mastery for Microsoft 365. Discover how AI can elevate your productivity in Excel, Word, and PowerPoint through real-world applications and hands-on exercises. Delve into Copilot 365 and harness the capabilities of Copilot Chat AI, offer.
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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!