Run customized LLM models on your system privately | Use ChatGPT like interface | Build local applications using Python
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Covers diverse model types including text, vision, and code generation, alongside creating custom models from .gguf files.
Includes the full Retrieval-Augmented Generation pipeline through document loading, chunking, and embedding using LangChain.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
This slide introduces the target audience for Ollama applications, illustrating developers, data scientists, and tech enthusiasts as key user groups.
This course overview slide introduces the topic of creating local LLM applications with Ollama, highlighting key learning objectives such as running models locally and understanding their capabilities.
This course features slide outlines that no prerequisites are required to start, while noting that basic knowledge of Python and Command Prompt is advantageous for learners.
This slide introduces the course instructors, Abhishek Bansal and Pukhraj Parikh, detailing their backgrounds in AI, analytics, and relevant industry experience.
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