Programming for Data Science

Instructor: Dr. Gregory Watson

• Syllabus

The Programming for Data Science course is aimed at providing students with the skills necessary to use Python for data analysis in scientific computing. In particular the course will cover:

• Python 3.5
• The NumPy package for scientific computing
• The pandas data analysis library, including reading and writing of CSV files
• The Jupyter and PyDev development environments
• The Matplotlib 2D plotting library
• Understanding the shell
• Using Git and GitHub
• Best-practice software engineering techniques

The course will be based on the excellent Software Carpentry curriculum and will incorporate pair-programming and live coding. The course will take a student-centered, active learning, approach to teaching this material. Class will typically consist of a short introductions to programming techniquess, followed by hands on computing exercises.