Mastering Semantic Kernel by Creating Projects

Overview

Do you want to integrate artificial intelligence into your applications efficiently and effectively? This course is your gateway to the world of Semantic Kernel, a powerful Microsoft tool that enables you to enhance your developments with language models (LLMs) like OpenAI and Azure OpenAI.

Syllabus

• Introduction to Semantic Kernel
Overview of Semantic Kernel
The role of Semantic Kernel in AI integration
Key features and benefits
• Setting Up Your Environment
Installation requirements
Configuring Semantic Kernel with OpenAI and Azure OpenAI
First project setup
• Understanding Language Models
Basics of Language Models (LLMs)
Application of LLMs in Semantic Kernel
Comparing OpenAI and Azure OpenAI models
• Core Concepts of Semantic Kernel
Data preprocessing and handling
Creating and utilizing templates
Integrating LLMs into applications
• Project 1: Building a Basic Application
Problem definition and planning
Step-by-step implementation with Semantic Kernel
Testing and evaluation
• Advanced Techniques
Fine-tuning language models
Creating custom solutions with Semantic Kernel
Error handling and optimization
• Project 2: Developing a Complex Solution
Designing advanced applications with Semantic Kernel
Incorporating multiple LLMs
Deployment strategies
• Integrating Semantic Kernel with Existing Applications
Interfacing Semantic Kernel with various platforms
Case studies and real-world examples
• Best Practices and Optimization
Performance tuning and scalability
Security considerations
Documentation and maintenance
• Future Trends and Developments
Emerging technologies in AI and LLMs
Future of Semantic Kernel and LLM applications
• Course Conclusion
Recap of key concepts
Final project presentations
Q&A and feedback session

Taught by

Héctor Uriel Pérez

Subjects

Computer Science