AI-3016 Develop copilots with Azure AI Studio

Price
Net €
VAT €

Price
Price on Request

Duration
1 day

For companies and job seekers:
this course is 100% fundable!

Location

Course Language
English

Training Solutions
Online Live

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Modern AI applications are changing the way digital assistants are developed, controlled, and integrated. Intelligent co-pilots based on Azure open up new possibilities for automation, efficiency, and context-sensitive interaction in corporate environments.

Key topics

Development of AI-based copilots with Azure AI Studio.
Use of large language models and prompt design.
Integration of data sources, APIs, and business logic.
Security, governance, and responsible AI.
Testing, optimization, and operation of copilot solutions.

Prerequisites
A basic understanding of cloud technologies and Azure services, as well as some experience with AI or software development, is recommended.

Target audience
IT professionals, developers, solution architects, and technically oriented roles who want to professionally plan and implement AI-powered assistants.

The content taught provides a solid foundation for building powerful copilots and supports the practical, secure, and scalable integration of AI strategies into modern system landscapes.

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course content

Introduction to Azure AI Studio

Learn about the key features and capabilities of Azure AI Studio.
Use Azure AI Studio to deploy and manage an Azure AI resource.
Use Azure AI Studio to create and manage an AI project.
Understand when to use Azure AI Studio.

Getting started with developing language model apps in Azure AI Studio with Prompt Flow

Understand the development cycle for creating language model applications.
Understand what a flow is in Prompt Flow.
Examine the core components when working with Prompt Flow.

Building a RAG-based Copilot solution with your own data using Azure AI Studio

Identifying the need to ground the language model with Retrieval Augmented Generation (RAG).
Indexing the data with Azure AI Search to make it searchable for language models.
Creating a copilot with RAG on your own data in Azure AI Studio.

Responsible generative AI in AI Studio

Describe an overall process for the responsible development of generative AI solutions.
Identify and prioritize potential harms relevant to a generative AI solution.
Measure the presence of harms in a generative AI solution.
Mitigate harms in a generative AI solution.
Preparing for the responsible deployment and operation of a generative AI solution.

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