Setup your own DeepSeek, Llama & other LLMs privately & securely. OpenWebUI based chat, no subscription & data sharing.
What you will learn
Learn to deploy, configure, and manage LLMs like DeepSeek and LLaMA using Open-WebUI and Ollama across AWS, GCP, and Azure with optimized performance.
Master API integration to embed LLMs in custom apps, automate workflows, and create AI-driven solutions with secure, efficient, and real-time data handling.
Optimize performance, allocate resources efficiently, and run multiple LLMs simultaneously for comparison, scalability, and faster inference speeds.
Gain expertise in using Ollamaβs command-line tools to download, manage, and update LLMs, automate tasks, and streamline model workflows effectively.
Why take this course?
This comprehensive course is designed to equip developers, AI enthusiasts, and enterprise teams with the skills needed to master large language models (LLMs) such as DeepSeek, LLaMA, Mistral, Gemma, and Qwen using Open-WebUI and Ollama. You will learn how to deploy, manage, and optimize these powerful models across various cloud platforms, including AWS, GCP, and Azure.
The course covers everything from foundational concepts to advanced implementation strategies. It begins with an overview of Open-WebUI and Ollama, introducing their intuitive interfaces and real-time capabilities. You’ll gain hands-on experience with setting up environments, integrating APIs, managing models through command-line interfaces, and running multiple models simultaneously for side-by-side evaluation.
Key benefits include understanding how to maintain data privacy, avoid vendor lock-in, and leverage cost-effective deployment strategies without the need for expensive GPU instances. Whether you’re developing AI applications, conducting LLM inference and evaluation, or seeking alternatives to commercial AI chat solutions, this course provides the tools and knowledge required to excel in the rapidly evolving world of LLMs. Additionally, you’ll gain insights into best practices for performance optimization, ensuring efficient resource utilization, and scaling AI applications seamlessly to meet diverse project requirements and business goals effectively, with greater benefits, accuracy, reliability, and speed.