course

NL/EN
This training is available in Dutch and English. More information

LLM Agent Development using Semantic Kernel

Use Semantic Kernel in C# to develop secure, scalable AI agents with testing and monitoring capabilities.

Not yet scheduled
- No location
-
2 days
1700 (excl. VAT)

Description

In this training, you will learn to use Semantic Kernel to leverage professional LLM Agents. Using a lot of hands-on exercises you will get familiar with the full scope of developing LLM Agents, including topics like LLMOps, prompt templates, API integrations, Retrieval Augmented Generation and memory management.

By the end of this training, you will be able to architect and develop secure, scalable AI agent systems using Semantic Kernel, with comprehensive testing and monitoring capabilities for business applications.

Learning Goals

CheckmarkUnderstand large language models, their capabilities, and how to select the right model for different use cases
UnderstandLogo InfoSupport
CheckmarkConstruct and configure Semantic Kernel applications with multiple AI connectors in both console and web environments
ApplyLogo InfoSupport
CheckmarkWrite effective prompts using templates, hyperparameters, and few-shot learning techniques
ApplyLogo InfoSupport
CheckmarkExplain the need for LLMOps practices including testing, monitoring, cost management, and security measures
UnderstandLogo InfoSupport
CheckmarkProduce chat-based applications using conversation history and streaming responses
ApplyLogo InfoSupport
CheckmarkImplement testing and monitoring for LLM applications using OpenTelemetry and standard unit-testing tools.
ApplyLogo InfoSupport
CheckmarkConstruct custom tools and functions that extend LLM capabilities, including external API integrations and filters
ApplyLogo InfoSupport
CheckmarkImplement Retrieval Augmented Generation (RAG) systems with vector stores for knowledge-enhanced AI applications
ApplyLogo InfoSupport
CheckmarkEmploy structured output generation using JSON formatting and sideband communication patterns
ApplyLogo InfoSupport
CheckmarkProduce production-ready AI agents with proper tool integration, memory management, and security constraints
ApplyLogo InfoSupport
For the above learning goals we use Bloom's Taxonomy

Prior Knowledge

  • Intermediate C# programming
  • Basic understanding of web APIs and json
  • Familiarity with cloud services

Subjects

  1. Introduction to Large Language Models
  2. Configuring Semantic Kernel Applications
  3. Effective prompting strategies
  4. LLMOps
  5. Building a chat-based application
  6. Implementing testing and monitoring using OpenTelemetry
  7. Extending LLM capabilities
  8. Retrieval Augmented Generation (RAG) systems and vector stores
  9. Structured output generation
  10. Production-ready AI agents

Schedule

All courses can also be conducted within your organization as customized or incompany training.

Our training advisors are happy to help you provide personal advice or find Incompany training within your organization.

Prior knowledge courses

"This training was immediately applicable to the project"
Attendee
  • icon

    Hoge waardering

  • icon

    Praktijkgerichte trainingen

  • icon

    Gecertificeerde trainers

  • icon

    Eigen docenten