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| title | Programming for Data Science |
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Instructor: Dr. Gregory Watson
- [Syllabus]({{ site.github.url }}/syllabus/programming-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.