Building AI Applications with Semantic Kernel and C#

Overview

Using AI services in .NET applications is becoming more and more popular but with all the different services out there, this task isn’t always easy. In this course, Building AI Applications with Semantic Kernel and C#, you’ll learn how to benefit from the Semantic Kernel library in your .NET apps.

First, you’ll explore the concepts and building blocks of Semantic Kernel. Next, you’ll discover how to create plugins to extend the capabilities of the underlying model easily.

Finally, you’ll learn how to use Semantic Kernel in a practical way inside your apps. When you’re finished with this course, you’ll have the skills and knowledge of the Semantic Kernel library needed to build powerful AI apps using .NET.

Syllabus

• Introduction to Semantic Kernel
Overview of AI services in .NET
Introduction to Semantic Kernel library
Importance and benefits of using Semantic Kernel
• Exploring Semantic Kernel Concepts and Building Blocks
Core components of Semantic Kernel
Understanding embeddings and vectors
Role of models within the Semantic Kernel framework
• Creating Plugins with Semantic Kernel
Introduction to plugins in Semantic Kernel
Steps to design and implement plugins
Extending model capabilities with custom plugins
• Practical Implementation with Semantic Kernel
Integrating Semantic Kernel into .NET applications
Best practices for efficient AI-powered features
Case study: Implementing a sample AI application
• Advanced Techniques and Optimization
Optimizing AI applications for performance
Troubleshooting common issues in Semantic Kernel applications
Future trends and updates in Semantic Kernel and AI services
• Course Summary and Next Steps
Recap of key learnings
Resources for further study and practice
Q&A and discussion on real-world application scenarios

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Taught by

Gill Cleeren

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Subjects

Computer Science