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Generative AI courses

911 Courses

California Institute of Technology Udemy

Social Engineering with AI: Advanced Techniques

Join our course, "Social Engineering with AI: Advanced Techniques," offered by Udemy, and delve deep into the world of advanced social engineering. Learn to master various techniques, from phishing to deepfakes, and discover how artificial intelligence is revolutionizing these modern manipulation tactics. This course is perfect for those who.
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California Institute of Technology AWS Skill Builder

Developing Generative Artificial Intelligence Solutions (日本語)

Developing Generative Artificial Intelligence Solutions (日本語) このコースでは、生成人工知能 (生成 AI) によるアプリケーションライフサイクルについて学びます。詳細は以下のとおりです。 ビジネスユースケースの定義 基盤モデル (FM) の選択 FM のパフォーマンスの改善 FM のパフォーマンスの評価 デプロイとビジネス目標への影響 このコースは生成 A.
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California Institute of Technology AWS Skill Builder

Exploring Artificial Intelligence Use Cases and Applications (日本語)

このコースでは、様々な産業領域における人工知能 (AI)、機械学習 (ML)、および生成AIの具体的なユースケースを探ります。これにはヘルスケア、金融、マーケティング、エンターテインメント業界が含まれ、AI技術の能力と限界、モデルの選択手法、主要なビジネスメトリクスを学びます。 コースレベル: 基礎 所要時間: 1時間 アクティビティこのコースは、インタラクテ.
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California Institute of Technology AWS Skill Builder

Responsible Artificial Intelligence Practices (日本語)

このコースでは、責任ある AI の実践について学びます。最初に、責任ある AI とは何かを説明します。責任ある AI の定義方法、直面している課題、その主な要素について学習します。 次に、責任ある AI システムを開発するためのトピックをいくつか取り上げます。責任ある AI をサポートするために AWS が提供しているサービスとツールを紹介します。また、AI システム用に.
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California Institute of Technology Coursera

Introduction to Generative AI with Snowflake

Explore the innovative realm of generative AI with a focused course using Snowflake. The program begins by introducing essential AI concepts, followed by a guided setup to create a functional learner environment and build a preliminary application. Progress to mastering Cortex LLM functions for executing diverse AI tasks, and culminate y.
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California Institute of Technology Udemy

Create docs & how-to guides using Generative AI with Guidde

Unlock the power of Generative AI to effortlessly craft expert documentation and how-to guides. Join our Udemy course aimed at empowering Product Owners and Product Managers to produce training materials, standard operating procedures (SOPs), and comprehensive guides with ease. Whether you're looking to enhance your technical writing skills o.
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California Institute of Technology Coursera

Microsoft Copilot for Excel: AI-Powered Data Analysis

This course provides a practical, project-oriented learning experience with Microsoft Copilot in Excel, allowing you to tackle real-world data analytics challenges. Begin by exploring the basics of Microsoft Copilot, including its capabilities and limitations, while comparing it to generative AI tools like ChatGPT. Learn how to set up Copilot.
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California Institute of Technology Udemy

Intro to Generative AI for Business Professionals

Udemy Delve into the world of Generative AI with our comprehensive course specifically tailored for business professionals. Learn how to harness AI technologies to drive innovation and streamline your business operations. This practical guide covers essential AI concepts and tools, including: Generative Adversarial Networks (GAN) Variat.
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California Institute of Technology DataCamp

AI Fundamentals

Embark on an exciting journey through the realms of Artificial Intelligence with DataCamp's AI Fundamentals course. This comprehensive program enables you to conquer AI frontiers and harness the power of generative AI and sophisticated large language models. Designed to lay a strong foundation, this course will propel you into the emerging A.
California Institute of Technology Udemy

A CEO's Generative AI Playbook

Discover the essential playbook for CEOs looking to integrate Generative AI into their business strategy. Offered by Udemy, this course offers a comprehensive guide to mastering the use of AI in a strategic context. You'll learn about Generative AI, Retrieval Augmented Generation (RAG), AI agents, and the integration of these advanced technolog.
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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!