Description
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.
Who this course is for:
- AI Enthusiasts & Developers: Those interested in deploying, managing, and integrating LLMs into applications.
- Data Scientists & Machine Learning Engineers: Professionals who want to experiment with different LLMs and optimize their performance.
- Cloud & DevOps Engineers: Individuals looking to set up and manage LLMs on AWS, GCP, or Azure efficiently.
- Tech Entrepreneurs & Startups: Anyone wanting to build AI-powered products without vendor lock-in or expensive GPU resources.
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