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

Created by: Start-Tech Academy
5,000,000+ Enrollments | 4.5 Rated | 160+ Countries

What Will I 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.

Requirements

• Basic Python knowledge and a computer capable of running Docker and Ollama are recommended, but no prior AI experience is required.

Target audience

• AI enthusiasts who want to build and run customized LLM models privately on their local systems.
• Python developers seeking to integrate large language models into local applications for enhanced functionality.
• Data scientists who aim to create secure, private LLM-powered tools without relying on cloud-based solutions.
• Machine learning engineers looking to explore and customize open-source models using Ollama and LangChain.
• Tech professionals who want to develop RAG (Retrieval-Augmented Generation) applications using local data.
• Privacy-conscious developers interested in running AI models with full control over data and environment.