Description
GenAI for .NET: Build LLM Apps with OpenAI and Ollama. This course teaches how to build generative AI (GenAI) applications using the .NET platform and Large Language Models (LLM) from OpenAI and Ollama. In this hands-on course, participants learn how to integrate various AI services including OpenAI, Azure AI, and Ollama using the Microsoft-Extensions-AI abstract libraries to create diverse applications such as chatbots, semantic search systems, retrieval-based augmentation (RAG) systems, and image analytics. The topics begin with an introduction to the .NET AI ecosystem and configuring model providers, and then move on to implementing tasks such as classification, summarization, data mining, and sentiment analysis with models such as GPT-5-mini and Llama3.2. Building an intelligent chatbot with the ability to maintain the conversation context and using Chat Streaming and Function Calling to call functions from other departments. The topic of vector search is fully covered by generating and storing text embeddings in a vector database such as Qdrant and performing semantic search. Also, implementing a RAG system to retrieve information from personal documents and produce accurate answers and image analysis with computer vision models for tasks such as object recognition and image caption generation is taught. Finally, all these concepts are integrated into a complete and practical project titled “Vector Searchable E-Store” using .NET Aspire for service orchestration, Qdrant and LLM models so that participants will gain the ability and confidence to develop intelligent GenAI applications at the end of the course.
What you will learn
- GenAI concepts: LLM, Token, SLM, Prompt Engineering.
- .NET + AI Ecosystem: AI development tools and libraries for .NET.
- Configuring LLM providers: GitHub Models, Ollama, Azure AI Foundry.
- Chat, Text Completions, Analysis and Function Calling with .NET.
- Completing the LLM text with the gpt-5-mini model from OpenAI’s GitHub Models.
- Classification, summarization, sentiment analysis, and other LLM use cases.
- Structured Output in LLM for data mining use.
- Building an AI chat application with .NET and the gpt-5-mini model.
- Calling .NET functions using the GH gpt-5-mini model with Function Calling.
- .NET AI vector search using Vector Embeddings and Vector Store.
- Generate Embeddings and calculate similarity with CosineSimilarity.
- Developing a .NET AI vector search application with Ollama and the all-minilm embedding model.
- Recovery Augmented Reality (RAG) based production application with .NET AI.
- Building a .NET chat application with the RAG Template using the OpenAI gpt-5-mini model.
- Building a .NET chat application with RAG Template using Ollama and all-minilm.
- Building an image analysis application with .NET and GH Models – OpenAI gpt-5-mini.
- Building an image analysis application with .NET and Ollama llava.
- Building an Eshop vector search application with .NET Aspire, gpt-5-mini, and Qdrant Vector DB.
- Adding the Qdrant vector database to .NET Aspire.
- Integrated AI building blocks: Microsoft Extensions AI (MEAI).
This course is suitable for people who:
- Developers and architects who are curious about developing LLM applications with .NET.
Course details
- Publisher: Udemy
- Instructor: Mehmet Ozkaya
- Training level: Beginner to advanced
- Training duration: 5 hours and 58 minutes
- Number of lessons: 64
Course syllabus as of 2025/9
Prerequisites for the GenAI for .NET: Build LLM Apps with OpenAI and Ollama course
- Basics of .NET Development
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: English
Quality: 720p
Download link
Downloadly
Rapidgator link
File(s) password: www.downloadly.ir
File size
2.9 GB
