Develop Custom Copilots with Azure AI Studio

Develop Custom Copilots with Azure AI Studio

Build Custom AI Solutions with Ease: Develop, Deploy, and Optimize Copilots Using Azure AI Studio

What does the Course Offer

7

12

16

12

10

Objectives

Practice Tests

Training Hours

Exercises

Knowledge Checks

This course focuses on developing custom copilots using Azure AI Studio, equipping participants with the skills to build intelligent, AI-powered assistants tailored to specific business needs. The course covers the complete development lifecycle, from setting up the AI environment to deploying responsible and effective copilots.

Course Overview

In this course, participants will learn how to develop custom AI copilots using Azure AI Studio, a powerful platform for building AI-driven assistants.

The course covers everything from setting up the AI environment to deploying sophisticated AI solutions that integrate with data sources, APIs, and external systems. Students will explore the process of creating effective conversational workflows, training AI models, and implementing advanced techniques like Retrieval, Augmentation, and Generation (RAG) to enhance copilot capabilities.

Learning Outcomes

• Prepare AI Hub: Set up and organize the AI environment in Azure AI Studio.

• Configure Connected Resources: Integrate data sources and APIs for copilot functionality.

• Explore and Deploy Models: Explore and deploy pre-built or custom AI models.

• Create Copilot Using Prompt Flow: Design and implement conversational workflows for copilots.

• Implement RAG (Retrieval, Augmentation, and Generation): Use RAG to enhance copilot responses with dynamic data.

• Configure Responsible AI: Apply ethical practices ensuring fairness, transparency, and accountability.

• Apply Custom Content Filters: Implement filters to provide safe, relevant, and accurate responses.

Audience Profile

• Aspiring AI professionals

• Business Analysts

• AI Developers

• Solution Architects

• Data Scientists

• Business Professionals

Prerequisites

• Familiarity with Azure and the Azure portal.

• Experience programming with C# or Python.

Course Objectives

• Prepare AI Hub

• Configure Connected resources

• Explore and Deploy Models

• Create Copilot using Prompt flow

• Implement RAG (Retrieval, Augmentation and Generation)

• Configure Responsible AI

• Apply Custom Content Filters

Format

Blended (Online Training + Discussions)

Streaming Platform

Microsoft Teams Online

Course Schedule

On Demand

Trainer

Kappagantula Srikanth

Duration

16 Hours

Course Fee

$1500

Course Outline

Prerequisites (1 Hour)

• Install Visual Studio

• Install Azure PowerShell & CLI

• Create/Access Microsoft Learn Account

• Create/Access GitHub Account

• Create/Access Microsoft Azure Account

• Create/Access Azure OpenAI Account

Prepare the AI hub

• Introduction to Azure AI Studio

• Create an Azure AI hub

• Create a new Azure AI project

• Add project users and assign roles

Configure connected resources

• Get started with prompt flow in Azure AI Studio

• Configure an Azure AI services or Azure OpenAI Service connection

• Configure an Azure AI Search connection

• Configure a storage connection

• Deploy and test a model

Explore and deploy models from the model catalog in Azure AI Studio

• Select an appropriate model and version from the Azure AI model catalog and collections

• Configure deployment settings

• Deploy a model

• Edit a deployed model

• Test a deployed model

Create a copilot by using prompt flow

• Get started with prompt flow in Azure AI Studio

• Create a chat flow

• Configure a language model node, including parameters and prompts

• Configure a Python node

• Configure a prompt node

• Define inputs and outputs

• Run and test the chat flow

Implement a Retrieval Augmented Generation (RAG) pattern

• Build a RAG-based copilot solution with your own data using Azure AI Studio

• Create a data component

• Create an index

• Integrate the data component and the index into the flow

• Test the index

• Run the chat application

Configure responsible AI

• Responsible generative AI

• Create a custom content filter

• Create an input filter that includes a blocklist

• Create an output filter with protected material

Apply a custom content filter to an existing deployment

• Evaluate the performance of your custom copilot in the Azure AI Studio

• Assess and compare copilot performance

• Assess a copilot by using built-in performance and quality metrics

• Assess a copilot by using built-in risk and safety metrics

• Assess a copilot by using manual evaluations

Enquire about the Course

You can also reach out to us through the following options

Phone

+65-91709407

Email

info@empowerone.cloud

WhatsApp Channel