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Develop AI Agents using Azure OpenAI and Semantic kernel
- Categories:
- Artificial Intelligence Cloud
- Level:
- Intermediate
- Code:
- MAZ2005
- Exam:
- Not Applicable
Overview
This course provides a comprehensive guide to building intelligent AI agents using Azure OpenAI and the Semantic Kernel SDK. Participants will learn to develop applications that automate tasks and perform natural language processing by integrating large language models with custom plugins and planners. The curriculum emphasizes practical skills in prompt engineering, plugin development, and responsible AI implementation, ensuring learners can create effective and ethical AI solutions.
Prerequisites
Participants should have:
- Experience programming in C#
- Visual Studio Code IDE installed
- Familiarity with Azure and the Azure portal
- Access to Azure OpenAI Services
Target audience
This course is suitable for:
- AI engineers, solution architects, and software developers
- Technical professionals interested in generative AI applications
- Organisations aiming to improve service automation and internal productivity with custom AI solutions
What's included
Select your preferred way to learn:
What is Virtual?
Live, instructor-led training delivered online
Interactive online sessions led by subject matter experts. Learners join live classes, take part in discussions, and complete practical exercises from any location, making it easy to fit collaborative learning into busy schedules.
If you prefer to connect to a course that is taking place in a physical classroom, you can choose our Remote Access option. .
Best for: Teams and individuals who want expert guidance, real-time collaboration, and flexible access.
What's included?
1 Day instructor led course
6 month free access to QA learning platform
Free 6-Month Access: Learning Platform Discovery plan
Included FREE with every instructor‑led course
Get free guided access to the QA Learning Platform. Assess your skills, explore in-demand topics, and understand which areas to focus on.
Learn AI, Cloud, Data, and Leadership skills at your own pace.
Put skills into practice with hands-on Labs and Simulabs.
Validate knowledge and highlight gaps with skills assessments.
What is bespoke training?
Custom instructor-led training designed by QA to fit your needs
Tailored programmes built around your organisation’s goals, challenges, and skill levels. Delivered in the format that suits you to maximise relevance and impact.
Best for: Organisations and teams looking to target specific business priorities and capabilities with QA subject matter expertise.
Find out more about the course:
Learning outcomes
By the end of this course, learners will be able to:
- Understand the purpose and capabilities of the Semantic Kernel SDK
- Develop and optimize prompts for AI interactions
- Create and integrate plugins to extend AI agent functionalities
- Implement native functions to provide skills to AI agents
- Combine prompts and functions to enhance AI responses
- Utilize planners to automate function calls and optimize workflows
- Develop a proof-of-concept AI application using the Semantic Kernel SDK
Course outline
Module 1: Build your kernel
- Introduction to Semantic Kernel
- Understanding the role of the kernel in AI applications
- Setting up the development environment
- Creating a kernel object
- Exercise: Build a kernel object
Module 2: Run prompts with Semantic Kernel
- Basics of prompt engineering
- Using prompt templates
- Implementing Handlebars prompt templates
- Storing and managing chat history
- Exercise: Use Semantic Kernel prompt templates
Module 3: Create Semantic Kernel plugins
- Understanding native plugins
- Developing native functions
- Configuring function choices
- Exercise: Create native functions
Module 4: Apply filters on functions
- Combining prompts and functions
- Implementing prompt injections
- Applying trust filters
- Filtering invoked functions
- Exercise: Add a filter service to the kernel
Module 5: Guided project - Create an AI travel agent
- Preparing for the guided project
- Developing a currency converter
- Creating a travel itinerary
- Providing context cues
- Exercise: Develop an AI travel assistant
Exams and assessments
There are no formal exams included in this course. Learners will complete interactive labs, guided exercises, and scenario-based tasks to reinforce understanding and assess their progress.
Hands-on learning
This course includes:
- Guided labs on kernel creation, prompt development, and plugin integration
- Practical exercises for implementing filters and planners
- Simulated real-world scenarios for developing AI applications
- Instructor feedback and collaborative learning activities
Good to know
Ready to book? Complete the form and a member of our team will be in touch shortly to discuss your options.
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What our customers are saying
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