Description. Azure OpenAI Technical Course

This course is taught in Online mode . The approximate duration of the course is 115 hours. that is distributes between content and collaboration tools. Upon completion, students will receive a certificate of completion.

Training is done through our Virtual Campus , with this modality you will have all the educational content on the course platform and it will be accessible, from the day the course starts, 24 hours a day, every day of the week. The student will also have participation forums, as well as ongoing tutoring.

The course fee applies to the virtual mode (100% bonus option) In-person and remote training actions can be carried out on demand.

• Access to the platform: 10 weeks
• Individualized support

Introduction

Learn how to implement Azure OpenAI technologies to develop your AI program. Our Azure OpenAI technical course covers how to use the Azure environment to set up the environment for advanced AI. Advance your career and take control of your AI program with the Azure OpenAI technical course.

This is a hands-on course to learn how to use Azure's general artificial intelligence service!

Addressed to

IT directors, ICT professionals, heads of innovation and development in the organization, managers from different departments who want to know how Artificial Intelligence can address their new technological expansion challenges with the help of OpenAI and Azure, innovation professionals, employees and all those who wish to learn about one of the main disruptive technologies today.

This course is aimed at professionals, students and AI enthusiasts who want to learn about and use the Azure OpenAI service, a cloud computing platform that offers access to state-of-the-art artificial general intelligence (AGI) models capable of performing various cognitive tasks from natural text input.

Course objectives

• Understand the basics of text generation with pre-trained language models and how they can be adapted to specific domains.
• Learn how to use custom Azure OpenAI to build, train, and manage GPT-4 fine-tuned models.
• Explore the creative possibilities and ethical limitations of text generation with GPT-4.
• Develop practical skills to implement and consume GPT-4 models from different platforms and programming languages.
• Apply the knowledge acquired in a final project that consists of generating texts on a topic chosen by the student.
• Explore the creative possibilities and ethical limitations of text generation with GPT-4.
• Develop practical skills to implement and consume GPT-4 models from different platforms and programming languages.
• Apply the knowledge acquired in a final project that consists of generating texts on a topic chosen by the student.

Course content

Unit 1: Introduction to Azure OpenAI Service

• Azure OpenAI Fundamentals: What it is, how it works, and what benefits it offers.
• Key concepts: Tokens, resources, deployments, models, and learning in context.
• Accessing Azure OpenAI: How to get an access key and how to use the Azure portal.
• Types of models in Azure OpenAI: what they are, how they are classified, and what characteristics they have.
• IAG Model Deployment - How to create and configure an Azure OpenAI model deployment.
• Using Messages to Get Model Completions - How to send and receive messages to a deployment to get results from a model.

Unit 2: Using Azure OpenAI Studio

• GPT-3, Davinci, Curie, Babbage and Ada models: what they are, how they differ and what applications they have.
• Codex and Cushman models: what they are, how they relate to GPT-3, and what uses they have in software development and text generation.
• Model tuning: what it is, how it is done and what benefits it has for customizing a model to the user's needs.
• How to manage content filtering: what it is, how to enable it, and how to configure it to avoid inappropriate or sensitive results.
• Creating a resource: How to create an Azure OpenAI resource and assign a model, plan, and region to it.
• Managing inserts: what they are, how they are used, and how to customize them to add additional information or modify the behavior of a model.
• Completions: what they are, how they are obtained and how the results of a model are interpreted.
• Using Code: How to use the Azure OpenAI SDK to interact with the service from different programming languages.
• Using Azure OpenAI Studio - How to use the Azure OpenAI web tool to create, test, and share IAG projects.
• Practice: Integrating Azure OpenAI into your application

Unit 3: Identity Management

• REST API: what it is, how to use it, and what advantages it has for integrating the Azure OpenAI service with other applications or services.
• Data encryption: what it is, how it is applied and what guarantees it offers to protect data privacy and security.
• Version control: what it is, how it is done and what benefits it has for maintaining a history of changes made to an IAG project.
• REST API Swagger - What it is, how to use it, and how it can help you document and test your Azure OpenAI REST API.

Unit 4: Managing an application with Azure OpenAI

• Understanding Messaging Engineering
• Writing more effective messages
• Context management to improve accuracy
• Using messaging engineering in the application

Unit 5: Generating code and images with Azure OpenAI Service

• Building code from natural language
• Using GitHub copilot
• Code completion and help in the development process
• Bug fixes and code improvements
• DALL-E integration in Azure OpenAI Studio
• Using Azure OpenAI REST API to consume DALL-E models
• Image generation

Laboratories

The course includes labs where you will learn how to make calls to an OpenAI implementation with pre-trained models from your own apps, understand the impact on model responses when correctly crafting questions (prompt engineering), write and improve code in different programming languages, programming using generative AI, creating images from natural language using DALL-E, and building your own AI virtual assistant capable of answering questions and referencing the answers in your organization's internal documentation.

Requirements

To take this course, you need to have a basic knowledge of artificial intelligence , as well as programming skills in one of the languages ​​supported by the Azure OpenAI SDK (Python, Java, C#, Node.js or Ruby). In addition, you need to have an Azure account and an access key to the Azure OpenAI service , which you can obtain for free for a limited period.