Data Science Fundamentals

INF80054 12.5 Credit Points


  • One semester or equivalent

Contact hours

  • 32 Hours

On-campus unit delivery combines face-to-face and digital learning.

2022 teaching periods


HB5  HE Block 5

11 Jul 22 - 21 Aug 22

27 Sep 22

Last self enrolment:
11 Jul 22

22 Jul 22

Last withdraw without fail:
5 Aug 22

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).