Learn OpenVINO
==============


.. meta::
   :description: Explore learning materials, including interactive
                 Python tutorials and sample console applications that explain
                 how to use OpenVINO features.


.. toctree::
   :maxdepth: 1
   :hidden:

   Interactive Tutorials (Python) <learn-openvino/interactive-tutorials-python>
   Sample Applications (Python & C++) <learn-openvino/openvino-samples>
   Large Language Model Inference Guide <learn-openvino/llm_inference_guide>



This section will help you get a hands-on experience with OpenVINO even if you are just starting
to learn what OpenVINO is and how it works. It includes various types of learning materials
accommodating different learning needs, which means you should find it useful if you are a beginning,
as well as an experienced user.

| :doc:`Tutorials <learn-openvino/interactive-tutorials-python>`
| A collection of interactive Python tutorials. It introduces you to the OpenVINO™ toolkit explaining how to use the Python API and tools for optimized deep learning inference. The tutorials are available in Jupyter notebooks and can be run in your browser. No installation required.

| :doc:`OpenVINO Samples <learn-openvino/openvino-samples>`
| The OpenVINO samples (Python and C++) are simple console applications that show how to use specific OpenVINO API features. They can assist you in executing tasks such as loading a model, running inference, querying particular device capabilities, etc.

| :doc:`Large Language Models in OpenVINO <learn-openvino/llm_inference_guide>`
| Detailed information on how OpenVINO accelerates Generative AI use cases and what models it supports. This tutorial provides instructions for running Generative AI models using Hugging Face Optimum Intel and Native OpenVINO APIs.
