Building Custom AI Copilots with Azure AI Studio

Build tailored AI copilots using Azure AI Studio’s language models and prompt flow

Duration

1 Day (8 hours)

Level

Basic Level

Design and Tailor this course

As per your team needs

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This course provides participants with a foundational understanding of how to design, develop, and deploy custom AI copilots using Azure AI Studio. Through hands-on exercises, attendees will learn how to configure, customize, and integrate AI copilots to serve specific organizational needs, enhancing productivity and supporting unique business applications.

By the end of this course, you will be equipped to design and deploy custom AI copilots using Azure AI Studio. You will gain practical skills in using language models, building RAG-based solutions, and applying responsible AI principles. These skills will empower you to build AI solutions tailored to your business needs.

Key Takeaways:

Understanding Azure AI Studio and its functionalities
Proficiency in developing language model-based applications
Ability to build AI copilots using your own data
Knowledge of responsible generative AI practices
Hands-on experience with RAG-based copilot solutions

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Developers, IT professionals, and business analysts interested in creating custom AI applications
Business leaders and project managers seeking to understand the potential of AI copilots to support business workflows
Technical professionals exploring Azure’s AI capabilities and looking to build or enhance their AI expertise

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Introduction to Azure AI Studio and Custom AI Copilots

Overview of Azure AI Studio
- Key features and capabilities of Azure AI Studio
- Overview of Azure OpenAI Service and its integration with Azure AI Studio
Understanding Custom AI Copilots
- Definition, use cases, and potential applications of AI copilots
- Examples of AI copilots in real-world scenarios across various industries
Basics of Prompt Engineering for Custom AI Copilots
- Best practices for creating effective, tailored prompts

Setting Up Your Azure Environment for AI Copilot Development

Setting Up Azure AI Studio
- Creating and managing an Azure AI Studio workspace
- Overview of Azure resources required for AI copilots
Configuring Data and Access for Copilot Projects
- Data integration requirements and best practices
- Ensuring proper data security, privacy, and access management

Designing Your Custom AI Copilot

Identifying Business Requirements and Use Cases
- Gathering functional requirements for the copilot
- Mapping use cases to AI capabilities: Natural language processing, decision support, etc.
Crafting the Interaction Model and Flow
- Designing effective prompts and responses for user interaction
- Structuring multi-step interactions and conversations for complex tasks

Developing and Testing Your AI Copilot in Azure AI Studio

Creating and Configuring the Copilot
- Step-by-step guide to building a copilot in Azure AI Studio
- Configuring parameters, responses, and user intent recognition
Integrating Azure OpenAI Services
- Leveraging OpenAI models (e.g., GPT) within the copilot framework
- Exercises: Testing prompt responses and refining AI outputs
Testing and Iteration for Enhanced Performance
- Best practices for testing, debugging, and improving copilot accuracy
- Role-play scenarios to fine-tune copilot responses

Deploying and Managing Custom AI Copilots

Deployment Options and Strategies
- Deploying copilots within an enterprise environment or specific business applications
- Options for integration with Microsoft 365, Teams, and other Azure services
Ongoing Management and Monitoring
- Monitoring copilot performance and user feedback
- Managing updates and continuous improvement based on usage patterns

Ethical AI and Best Practices for Custom Copilots

Principles of Responsible AI
- Fairness, transparency, and ethical considerations in AI interactions
- Ensuring data privacy and user trust
Best Practices for User Experience in AI Copilots
- Creating clear, helpful, and non-intrusive copilot interactions
- Tips for maintaining user engagement and satisfaction with AI solutions

Hands-On Workshop and Case Study

Workshop: Developing a Custom AI Copilot
- Participants will create a basic AI copilot to fulfill a common business need, such as customer support, HR assistance, or sales enablement
- Review and refine copilots based on peer and instructor feedback
Case Study: Analyzing a Real-World Copilot Use Case
- Discuss key takeaways and challenges from real-world custom AI copilot projects

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Basic understanding of AI concepts
Familiarity with Azure services
Completion of “Getting Started with Artificial Intelligence” learning path (recommended)

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Building Custom AI Copilots with Azure AI Studio

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