Data Science Fundamentals

INF80054 12.5 Credit Points


  • One semester or equivalent

Contact hours

  • 32 Hours

2021 teaching periods


HB1  HE Block 1

8 Feb 21 - 21 Mar 21

4 May 21

Last self enrolment:
8 Feb 21

19 Feb 21

Last withdraw without fail:
5 Mar 21

Aims and objectives

This unit will give students a solid foundation in contemporary data science best practices using Python. It will cover a hands-on introduction to programming paradigms and fundamental data analysis techniques. Through examples involving real-world data, students will learn data cleaning and validation techniques, data transformation procedures, algorithm design, text analytics, and data visualisation techniques. Students will become familiar with important Python software modules such as Pandas, Matplotlib, and the Natural Language Toolkit (NLTK).