The Programming for Data Science course unit aims at introducing the basics of programming in Python for Data Scientists. The course is oriented to students that do not have any experience in computer programming, starting from the very basics of computation. However, the course will rapidly evolve towards advanced programming techniques and concepts. In this way, at the end of this course unit, the students will be able to effectively approach complex problems, typically characterized by vast amounts of data, programming efficient strategies to extract information and support decision-making processes.
Classes will involve a mix of lectures and practical exercises. Moreover, the course will have a strong active learning component, as such students are expected to actively participate in the class and read the recommended materials prior to each class. A short introduction to Python will be delivered in the first weeks of the course to enable students to explore and practice many of the theoretical concepts taught in the classes. Bibliography
- Lubanovic, Bill. Introducing Python: modern computing in simple packages.” O’Reilly Media, Inc.”, 2014;
- VanderPlas, Jake. Python data science handbook: essential tools for working with data.” O’Reilly Media, Inc.”, 2016.
- McKinney, Wes. Python for data analysis: Data wrangling with Pandas, NumPy, and IPython.” O’Reilly Media, Inc.”, 2012
- Grus, Joel. Data science from scratch: first principles with python. “ O’Reilly Media, Inc.”, 2015