Data Science Fundamentals

INF80054 12.5 Credit Points

Duration

  • One semester or equivalent

Contact hours

  • 32 Hours

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

2022 teaching periods

Hawthorn

HB1  HE Block 1 HB5  HE Block 5

Dates:
7 Feb 22 - 20 Mar 22

Results:
3 May 22

Last self enrolment:
7 Feb 22

Census:
18 Feb 22

Last withdraw without fail:
4 Mar 22

Dates:
11 Jul 22 - 21 Aug 22

Results:
27 Sep 22

Last self enrolment:
11 Jul 22

Census:
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).