INFO634-19S2 (C) Semester Two 2019

Special Topic

15 points

Start Date: Monday, 15 July 2019
End Date: Sunday, 10 November 2019
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Friday, 26 July 2019
  • Without academic penalty (including no fee refund): Friday, 27 September 2019


Special Topic


This course aims to help students develop an understanding of data science/ analytics, and provide an opportunity to gain experience with diverse methods and technologies related to common aspects of data science/analytics. Key concepts, analytical techniques and tools applicable to different aspects of data science/analytics and business decision making (i.e. business intelligence (BI)) are introduced.

Students completing this course have an opportunity to develop foundational skills in the use of common data science/analytics tools, including data handling, data visualization, regression, neural networks, decision trees, time series analysis, and exploratory data analysis, and apply these to decision-making in organisations.

Learning Outcomes

At the end of this course, students will be able to:
1. Demonstrate an understanding of key data science/analytics concepts, tools and techniques
2. To recognise and analyse business problems and opportunities related to the role and use of data science/ analytics in organisations
3.  To select and apply suitable techniques (e.g. forecasting, data mining), extract meaningful insights from various data, and make recommendations that align with the organisations’ context/objectives and business decisions.
4. Produce appropriate information models and reports for use in business decision-making using Data Science/ Analytics software/visualisation tools
5. Work as a team to perform key activities related to the analysis of data and business decisions and provision of meaningful insights (BI) and evidence-based recommendations.


Subject to approval of the Head of Department

Timetable 2019

Students must attend one activity from each section.

Computer Lab A
Activity Day Time Location Weeks
01 Wednesday 15:00 - 18:00 Ernest Rutherford 464 Computer Lab
15 Jul - 25 Aug
9 Sep - 20 Oct
Computer Lab B
Activity Day Time Location Weeks
01 Tuesday 10:00 - 12:00 Rehua 008 Computer Lab 12 Aug - 25 Aug
9 Sep - 15 Sep

Examination and Formal Tests

Test A
Activity Day Time Location Weeks
01 Wednesday 13:00 - 16:00 Ernest Rutherford 212 Computer Lab 7 Oct - 13 Oct

Course Coordinator

Annette Mills


Assessment Due Date Percentage 
Assignments 10%
Individual Essay 20%
Project 30%
Final Test 40%

Indicative Fees

Domestic fee $975.00

* Fees include New Zealand GST and do not include any programme level discount or additional course related expenses.

Minimum enrolments

This course will not be offered if fewer than 5 people apply to enrol.

For further information see Department of Accounting and Information Systems on the department and colleges page.

All INFO634 Occurrences

  • INFO634-19S2 (C) Semester Two 2019