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

    COMP151 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. COMP151 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.

    About this paper

    Paper title Programming for Scientists
    Subject Computer and Information Science
    EFTS 0.1500
    Points 18 points
    Teaching period Semester 1 (On campus)
    Domestic Tuition Fees ( NZD ) $1,173.30
    International Tuition Fees Tuition Fees for international students are elsewhere on this website.
    COMP 150
    Schedule C
    Arts and Music, Commerce, Science

    Dr Yawen Chen

    Teaching staff

    Dr Yawen Chen

    Associate Professor Haibo Zhang

    Reuben Crimp (labs)

    Paper Structure

    Two Lectures and two labs per week.
    Programming is a skill that requires incremental mastery of concepts. Therefore, COMP151 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


    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 9-13, 15-22
    A2 Tuesday 09:00-10:50 9-13, 15-22
    A3 Wednesday 10:00-11:50 9-13, 15-22
    AND one stream from
    B1 Thursday 12:00-13:50 9-13, 15-16, 18-22
    B2 Thursday 14:00-15:50 9-13, 15-16, 18-22
    B3 Friday 14:00-15:50 9-12, 15-22


    Stream Days Times Weeks
    A1 Monday 10:00-10:50 9-13, 15-22
    Wednesday 14:00-14:50 9-13, 15-22
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