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COMP151 Programming for Scientists

An introduction to the basics of programming using the Python programming language, with an emphasis on programming of relevance to scientists.

COMP 151 introduces programming in a way that is targeted towards the needs of scientists and those working with data. Although the paper is called "Programming for Scientists", it is equally useful for anyone interested in programming in general, or in programming with data specifically. COMP 151 uses the Python programming language which is the most popular language for data science applications, and the 3rd most popular language overall and continues to grow in popularity.

Paper title Programming for Scientists
Paper code COMP151
Subject Computer and Information Science
EFTS 0.1500
Points 18 points
Teaching period Semester 1 (On campus)
Domestic Tuition Fees (NZD) $1,141.35
International Tuition Fees Tuition Fees for international students are elsewhere on this website.

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COMP 150
Schedule C
Arts and Music, Commerce, Science

Professor Brendan McCane:

Teaching staff

Professor Brendan McCane:
Karen Gray:

Paper Structure

Two Lectures and two labs per week.
Programming is a skill that requires incremental mastery of concepts. Therefore, COMP 151 uses the mastery model of learning and is 100% internally assessed.


The course workbook is available free online for enrolled students or can be printed at cost.

Graduate Attributes Emphasised
Interdisciplinary perspective, Lifelong learning, Communication, Critical thinking, Cultural understanding, Ethics, Information literacy.
View more information about Otago's graduate attributes.
Learning Outcomes

By completion of this paper students are expected to:

  • Understand fundamental concepts relating to computer programming
  • Demonstrate the ability to write small computer programs
  • Develop an understanding of the basic needs of scientific programming including but not limited to: data input and output, data manipulation, and data visualisation
  • Develop a basic understanding of ethical and best practice issues associated with collecting and storing data, including indigenous data

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Semester 1

Teaching method
This paper is taught On Campus
Learning management system

Computer Lab

Stream Days Times Weeks
Attend one stream from
A1 Monday 14:00-15:50 9-14, 16-22
A2 Tuesday 09:00-10:50 9-14, 16, 18-22
A4 Wednesday 10:00-11:50 9-14, 16-22
AND one stream from
B1 Thursday 12:00-13:50 9-14, 16-22
B2 Thursday 14:00-15:50 9-14, 16-22
B4 Friday 14:00-15:50 9-13, 16-22


Stream Days Times Weeks
A1 Monday 09:00-09:50 9-14, 16-22
Wednesday 14:00-14:50 9-14, 16-22