This workshop series will present an extensive discussion on how to improve the performance of Python in data science by looking under the hood of its language/libraries and using the technologies to make Python a practical solution for the high-performance big data analytics. In the first session, we will focus on how to boost the speed of python code in an interperter level by explaining the concepts (e.g. GIL, GIT) and introducing the packages of pypy, numba, pythran, cython etc. Although no specific prerequisite is required to attend the talk, having programming experience in Python will be helpful to fully understand the lecture content.