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Generative AI courses

755 Courses

California Institute of Technology Udemy

Generative AI for Professionals and Leaders

Advance your professional journey with the course "Generative AI for Professionals and Leaders" offered by Udemy. This comprehensive learning experience is designed to help you excel in your career by effectively leveraging Generative AI. Dive into essential areas such as Learning, Implementation, Change Management, and the establishment of a G.
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California Institute of Technology Udemy

OCI AI Foundations Associate 1Z0-1122-24 Exam Preparation

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California Institute of Technology Udemy

AI Security Essentials

Unlock the necessary skills to protect artificial intelligence systems with the "AI Security Essentials" course, available on Udemy. This program delves into critical aspects needed to secure AI technologies and emphasizes practical applications across various domains. Categorized under Anomaly Detection, Generative AI, ChatGPT, Cybersecurity.
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California Institute of Technology Udemy

GenAI for Professionals: 10x Your Productivity

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California Institute of Technology Udemy

Generative AI and ChatGPT Masterclass for Software Engineers

Elevate your skills with the Generative AI and ChatGPT Masterclass tailored specifically for software engineers. This comprehensive course offers the perfect blend of theoretical underpinnings and practical know-how. Explore AWS Gen AI, Bedrock, and Gemini through immersive, hands-on training sessions. Whether you're just starting or looking.
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California Institute of Technology Udemy

Azure AI Studio - Complete Guide to Azure AI Studio Copilot

Elevate your expertise in AI with our comprehensive Azure AI Studio - Complete Guide to Azure AI Studio Copilot. This masterclass offered by Udemy equips you with the knowledge to build innovative Generative AI applications and copilots. Discover how to automate tasks effectively using Gen AI, delve into Retrieval Augmented Generation (RAG), a.
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California Institute of Technology Udemy

AI | GenAI | AWS | Amazon Q Business | Create ChatGPT | 2024

Gain expertise in AI with our comprehensive course, AI | GenAI | AWS | Amazon Q Business | Create ChatGPT | 2024. This course empowers you to harness the full capabilities of AWS GenAI in conjunction with Amazon Q Business, making AI accessible and beneficial to all departments, including IT, HR, and Operations. Offered by Udemy, this course w.
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California Institute of Technology Udemy

Python Mastery with Tabnine: AI-Enhanced Coding Efficiency

Unlock the potential of AI-enhanced coding with our course on Python Mastery with Tabnine. Designed for software developers looking to accelerate their coding processes, Tabnine offers whole-line and full-function code completions that streamline your programming tasks. Hosted on Udemy, this course falls under multiple categories to provide a c.
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California Institute of Technology Udemy

LLM Mastery: Hands-on Code, Align and Master LLMs

Course Title: LLM Mastery: Hands-on Code, Align and Master LLMs Provided by: Udemy Course Overview: Embark on a comprehensive journey into the world of Large Language Models (LLMs) with our hands-on course. Designed for deep learning enthusiasts and professionals, this course demystifies the process of coding and aligning LLMs from the ground u.
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California Institute of Technology Udemy

LLM Engineering: Master AI & Large Language Models (LLMs)

Embark on a groundbreaking journey into the world of AI with our LLM Engineering course. Designed by experts, this course equips you with the skills necessary to become a proficient LLM Engineer in just 8 weeks. Throughout the course, you'll build and deploy eight innovative LLM applications, gaining hands-on experience that solidifies your.
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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!