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Generative AI courses

542 Courses

California Institute of Technology AWS Skill Builder

Créer un bot qui réponde aux questions à l'aide de l'IA générative (Français) | Build a Question-answering Bot using Generative AI (French)

Créer un bot qui réponde aux questions à l'aide de l'IA générative (Français) | Build a Question-answering Bot using Generative AI (French) Dans cet atelier, vous allez créer un chatbot qui répond aux questions concernant les services AWS. Cet atelier est destiné à vous fournir une expérience pratique dans le déploiement d’un grand modèle de lang.
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California Institute of Technology AWS Skill Builder

Cree un bot de búsqueda de respuestas mediante la IA generativa (Español LATAM) | Build a Question-answering Bot using Generative AI (LATAM Spanish)

Cree un bot de búsqueda de respuestas mediante la IA generativa (Español LATAM) | Build a Question-answering Bot using Generative AI (LATAM Spanish) Información general del laboratorio En este laboratorio, creará un chatbot que responde preguntas sobre los servicios de AWS. El laboratorio está diseñado para proporcionarle experiencia práctica.
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California Institute of Technology AWS Skill Builder

Building a Generative AI-Ready Organization (Korean)

Building a Generative AI-Ready Organization (Korean) 비즈니스 및 기술 의사 결정권자를 위한 생성형 AI Essentials 3부 시리즈의 마지막 과정인 Building a Generative AI-Ready Organization입니다. 아직 완료하지 않았다면 시리즈의 첫 번째 과정인 Introduction to Generative AI: Art of the Possible부터 시작하는 것을 권장합니다. 이 과정을 마치면 생성형 AI에 대.
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California Institute of Technology AWS Skill Builder

Introduction to Generative AI - Art of the Possible (Thai)

Introduction to Generative AI - Art of the Possible (Thai) หลักสูตรความรู้เบื้องต้นเกี่ยวกับ Generative AI - ศิลปะของความเป็นไปได้ จะให้ความรู้เบื้องต้นเกี่ยวกับ Generative AI กรณีใช้งาน ความเสี่ยง และข้อดี ด้วยตัวอย่างการสร้างเนื้อหา เราสามารถแสดงให้เห็นถึงศิลปะของความเป็นไปได้ เมื่อจบหลักสูตร ผู้เรียนควรจะสามารถอธิบายพื้นฐานของ Generative AI รวมถ.
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California Institute of Technology AWS Skill Builder

Building a Generative AI-Ready Organization (Indonesian)

Building a Generative AI-Ready Organization (Indonesian) Building a Generative AI-Ready Organization adalah kursus terakhir dari rangkaian tiga bagian Generative AI Essentials for Business and Technical Decision Makers. Jika Anda belum melakukannya, kami sarankan Anda memulai dengan kursus pertama dalam seri ini, Introduction to Generative AI: Ar.
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California Institute of Technology AWS Skill Builder

Introduction to Generative AI - Art of the Possible (Indonesian)

Introduction to Generative AI - Art of the Possible (Indonesian) Kursus Introduction to Generative AI - Art of the Possible memberi pengantar ke AI generatif, kasus penggunaan, risiko dan manfaat. Dengan bantuan contoh pembuatan konten, kami mengilustrasikan seni kemungkinan. Pada akhir kursus, pemelajar harus bisa menjelaskan dasar-dasar AI gene.
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California Institute of Technology AWS Skill Builder

Building a Generative AI-Ready Organization (Japanese)

Building a Generative AI-Ready Organization (Japanese) “Building a Generative AI-Ready Organization” は “Generative AI Essentials for Business and Technical Decision Makers” という 3 部構成のシリーズの最後のコースです。未履修の場合は、シリーズの最初のコース “Introduction to Generative AI: Art of the Possible” から始めることをお勧めします。 このコ.
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California Institute of Technology AWS Skill Builder

Building a Generative AI-Ready Organization (Vietnamese)

Building a Generative AI-Ready Organization (Vietnamese) Building a Generative AI-Ready Organization là khóa học cuối cùng trong chuỗi khóa học gồm ba phần có tên Generative AI Essentials for Business and Technical Decision Makers. Chúng tôi khuyên bạn nên bắt đầu với khóa học đầu tiên trong chuỗi khóa học này, Introduction to Generative AI: Art.
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California Institute of Technology Codecademy

Streamline Resume Creation with Generative AI Case Study

Streamline Resume Creation with Generative AI Case Study Discover how to use generative AI to streamline the creation of a custom resume, ensuring it is tailor-made to a specific job application and packed with relevant keywords for improved discoverability. This case study is designed to enhance your skills in leveraging generative AI for resum.
California Institute of Technology Codecademy

Unit Testing with Generative AI Case Study

Unit Testing with Generative AI Case Study Use generative AI to help create a unit test for Python code. Generative AI can generate unit tests for all functions of a Python class. In this case study, you will develop your skills in using generative AI to assist you in writing unit tests for Python code. We will provide you with a sample Python.

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!