Was Sie vorher wissen sollten
bevor Sie beginnen

Beginnt 5 June 2026 01:45

Endet 5 June 2026

00 Tage
00 Stunden
00 Minuten
00 Sekunden
course image

Mastering Semantic Kernel by Creating Projects

Dive into the transformative world of Semantic Kernel with our course, "Mastering Semantic Kernel by Creating Projects." Discover how to harness the capabilities of Semantic Kernel to build advanced AI applications using the robust tools of OpenAI and Azure OpenAI. This course is designed for enthusiasts and professionals looking to deepen.
via Udemy

4160 Kurse


8 hours 28 minutes

Optionales Upgrade verfügbar

Not Specified

Lernen Sie in Ihrem eigenen Tempo

Paid Course

Optionales Upgrade verfügbar

Übersicht

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.

Lehrplan

  • 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

Unterrichtet von

Héctor Uriel Pérez


Fachgebiete

Computer Science