Learn about high-level GPU programming in NumbaPro to reduce development time and produce high-performance data-parallel code with the ease of Python. This tutorial is for beginning to intermediate CUDA programmers who already know Python. In this tutorial, audience will learn about (1) high-level Python decorators that turn simple Python functions into data-parallel GPU kernels without any knowledge of the CUDA architecture; (2) CUDA library bindings that can be used as a drop-in to speedup existing applications; and, (3) reuse existing CUDA-C/C++ code in Python with JIT Linking.