Create Powerful Local LLM Applications with Python

In today’s world, the ability to harness the power of Large Language Models (LLMs) without relying on the cloud is invaluable. “Build local LLM applications using Python and Ollama” offers a comprehensive overview for developers, data scientists, and AI enthusiasts eager to explore LLMs securely and privately right from their local machines. This course is your gateway to crafting applications that maintain complete control over your data and workflow.

Throughout this course, you will learn to set up Ollama and deploy the Llama LLM model for local use. With an emphasis on hands-on experience, step-by-step tutorials will guide you through customizing your LLM models and developing Python-based applications that integrate seamlessly with Ollama’s REST API. Additionally, you’ll dive deep into advanced topics, including building Retrieval-Augmented Generation (RAG) systems that efficiently process large documents and enhance your application’s capabilities.

What makes this course truly unique is its focus on privacy, flexibility, and practical implementation. By leveraging tools like Ollama and LangChain, you will gain the necessary skills to create sophisticated LLM applications that meet your specific needs—ensuring that your data remains private and within your control. By the end of the course, you’ll be equipped to develop secure AI solutions that open up new possibilities for your projects. Are you ready to take the plunge into local LLM development? Enroll now to start your journey!

What you will learn:

• Download and install Ollama for running LLM models on your local machine
• Set up and configure the Llama LLM model for local use
• Customize LLM models using command-line options to meet specific application needs
• Save and deploy modified versions of LLM models in your local environment
• Develop Python-based applications that interact with Ollama models securely
• Call and integrate models via Ollama’s REST API for seamless interaction with external systems
• Explore OpenAI compatibility within Ollama to extend the functionality of your models
• Build a Retrieval-Augmented Generation (RAG) system to process and query large documents efficiently
• Create fully functional LLM applications using LangChain, Ollama, and tools like agents and retrieval systems to answer user queries

Course Content:

• Sections: 6
• Lectures: 27
• Duration: 2h 1m

Requirements:

• Basic Python knowledge is recommended
• No prior AI experience is required

Who is it for?

• Software developers who want to build and run private LLM applications on their local machines
• Data scientists looking to integrate advanced LLM models into their workflow without relying on cloud solutions
• Privacy-focused professionals who need to maintain complete control over their data while leveraging powerful AI models
• Tech enthusiasts interested in exploring local LLM setups using cutting-edge tools like Ollama and LangChain

What are you waiting for to get started?

Enroll today and take your skills to the next level. Coupons are limited and may expire at any time!

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