Zero to Hero in Ollama: Create Local LLM Applications
Run customized LLM models on your system privately | Use ChatGPT like interface | Build local applications using Python
4.51 (251 reviews)
7,808
students
3 hours
content
Feb 2025
last update
$69.99
regular price
What you will learn
Install and configure Ollama on your local system to run large language models privately.
Customize LLM models to suit specific needs using Ollama’s options and command-line tools.
Execute all terminal commands necessary to control, monitor, and troubleshoot Ollama models
Set up and manage a ChatGPT-like interface using Open WebUI, allowing you to interact with models locally
Deploy Docker and Open WebUI for running, customizing, and sharing LLM models in a private environment.
Utilize different model types, including text, vision, and code-generating models, for various applications.
Create custom LLM models from a gguf file and integrate them into your applications.
Build Python applications that interface with Ollama models using its native library and OpenAI API compatibility.
Develop a RAG (Retrieval-Augmented Generation) application by integrating Ollama models with LangChain.
Implement tools and agents to enhance model interactions in both Open WebUI and LangChain environments for advanced workflows.
Screenshots
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udemy ID
9/12/2024
course created date
9/23/2024
course indexed date
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