Packt

GenAI for .NET: Build LLM Apps with OpenAI and Ollama

Packt

GenAI for .NET: Build LLM Apps with OpenAI and Ollama

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Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Intermediate level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Implement LLM and SLM-based text generation and analysis in .NET applications.

  • Build vector search and semantic search solutions using embeddings and vector databases.

  • Develop retrieval-augmented generation (RAG) apps integrating external knowledge sources.

  • Deploy AI solutions locally with Ollama and cloud models using OpenAI and Azure services.

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Recently updated!

July 2026

Assessments

10 assignments

Taught in English

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There are 10 modules in this course

In this module, we will introduce the course and outline what you will learn about building LLM applications using .NET. We will review prerequisites, source code, and course slides to support your learning. Finally, we will explore the range of practical projects you’ll develop throughout the course.

What's included

3 videos1 reading

In this module, we will learn the fundamentals of generative AI, including LLMs and SLMs. We will explore tokens, tokenization, and how prompts guide model behavior. By the end, you will understand how to engineer prompts to produce accurate and efficient AI outputs.

What's included

5 videos1 assignment

In this module, we will explore the .NET ecosystem for AI development, including frameworks and SDKs. We will dive into Microsoft.Extensions.AI for unified AI building blocks. Additionally, you will learn how to use Semantic Kernel to add semantic intelligence to your .NET applications.

What's included

4 videos1 assignment

In this module, we will review AI providers including GitHub models, Ollama, and Azure AI Foundry. You will learn how to set up access credentials and download models locally. By the end, you will be ready to run LLMs both in the cloud and on your local environment.

What's included

6 videos1 assignment

In this module, we will build practical AI applications in .NET, including chat apps and text completion tools. We will explore real-time streaming, classification, summarization, and structured data extraction. Additionally, you will learn how to invoke functions from LLMs to expand application functionality.

What's included

10 videos1 assignment

In this module, we will dive into vector embeddings and vector databases for AI-driven search. You will generate embeddings, store them in-memory, and perform vector searches. By the end, you will develop a .NET vector search app capable of retrieving highly relevant results.

What's included

9 videos1 assignment

In this module, we will explore Retrieval-Augmented Generation (RAG) and its application in .NET chat apps. You will learn how to integrate external knowledge and extend chat functionality with custom documents and function calling. Additionally, you will incorporate vector databases to enhance data retrieval.

What's included

10 videos1 assignment

In this module, we will develop AI-powered image analysis applications in .NET. You will work with both cloud-hosted and local models to perform recognition tasks. By the end, you will be able to generate structured outputs from images for various use cases.

What's included

5 videos1 assignment

In this module, we will build a full-featured EShop vector search application using .NET Aspire. You will integrate chat, semantic search, and vector databases into a distributed microservices architecture. Finally, you will develop both front-end and back-end components for a production-ready AI application.

What's included

17 videos1 assignment

In this module, we will wrap up the course with a summary of what you have learned. You will review key concepts and project outcomes. Finally, we will outline next steps to continue building advanced AI applications with .NET.

What's included

1 video2 assignments

Instructor

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