Programming for Data Science

The teaching activity takes place in class or via videoconference, with exposure to concepts, techniques and methods,with a strong focus on solving practical problems. Software will be used to support problem solving. The student willbe evaluated by a work assignment and a final written exam, both with the same weight in the final grade. The grade ofthe work will only be considered if the student obtains a minimum grade of 8 in the written test (on a scale of 0 to 20).

The Programming for Data Science course unit is intended for students without previous programming experience. It isa structuring unit of the master’s course in data analysis and decision support systems as students will learn thefundamentals of programming in Python necessary to carry out programming activities in other curricular units anddevelop Data Science projects. In this curricular unit after a brief introduction to the concepts of algorithm andprogramming the students will gain contact with the base libraries for the realization of Data Science projects, such asNumPy, Pandas, MatPlotLib, Scipy, Scikit-learn. In addition to these libraries, they will learn how to manipulate datasets with the SQL language. This curricular unit is intended to allow the student to gain a set of skills that will allowhim/her to autonomously carry out programming and development activities of Data Science projects.

1 – Basics of Python
2 – Python Data Structures
3 – Python Programming Basics
4 – Working with data in Python
5 – Python data visualization
6 – Introduction to learning machines in Python
7 – Other Python applications

NAO