Course level

Postgraduate Coursework

Faculty

Science

School

School of the Environment

Units

2

Duration

One Semester

Class hours

Lecture 5 Hours/ Week
Problem-based learning 6 Hours/ Week
5L 6PBL

Assessment methods

Examination, quizzes, practical skills assessment

Course enquiries

Dr Jan Engelstaedter (j.engelstaedter@uq.edu.au)

Current course offerings

Course offerings Location Mode Course Profile
Semester 1, 2024 (30/01/2024 - 23/03/2024) External External Course Profile
Semester 1, 2024 (30/01/2024 - 23/03/2024) St Lucia In Person Course Profile

Please Note: Course profiles marked as not available may still be in development.

Course description

This course will provide students with a thorough introduction to two programming languages that are widely used within the biological sciences: Python and R. No prior knowledge of any programming language is required. The course will be taught in a workshop-style manner over 15 consecutive days. Each day starts with an informal lecture interspersed with exercises, following which students will work on a range of small to medium-scale projects directly related to the lecture content. The first module will provide an introduction to the statistical programming language R, which will be followed by a module teaching programming in Python. Both modules will focus on data science task commonly encountered in biology and other life sciences. Topics to be covered in these two modules include basic syntax, data import, export and manipulation, flow control, statistical analysis, string manipulation and data visualisation. Examples and projects will cover a variety of real biological datasets and problems. The course concludes with an introduction to the Unix/Linux environment (including some shell scripting), version control using git, regular expressions and high performance computing. At the end of this course, students will not only be fluent in two important programming languages but will also have acquired an understanding of general coding principles that will enable them to read and adapt code in other programming languages. This course provides the foundation for all other courses within the Master of Quantitative Biology program that will use R and Python throughout.

Archived offerings

Course offerings Location Mode Course Profile
Semester 1, 2023 (30/01/2023 - 25/03/2023) External External Course Profile
Semester 1, 2023 (30/01/2023 - 25/03/2023) St Lucia In Person Course Profile
Semester 1, 2022 (31/01/2022 - 26/03/2022) External External Course Profile
Semester 1, 2022 (31/01/2022 - 26/03/2022) St Lucia Internal Course Profile
Summer Semester, 2020 (04/01/2021 - 30/01/2021) St Lucia Intensive Course Profile