DATA101-24S2 (C) Semester Two 2024

Introduction to Data Science

15 points

Details:
Start Date: Monday, 15 July 2024
End Date: Sunday, 10 November 2024
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 28 July 2024
  • Without academic penalty (including no fee refund): Sunday, 29 September 2024

Description

Data Science is a fast growing, important, and globally in-demand discipline. This course is designed to introduce students to the fundamentals of this field. It will start by introducing key mathematical and statistical concepts and applications like exploratory data analysis, probability (with a focus on essential theories, discrete and continuous random variables), modelling, inference, and bivariate data. It will also address a range of more applied topics where data is important to making decisions, including data wrangling, data analysis, and data visualisation, supported by the statistical programming language R.

Learning Outcomes

University Graduate Attributes

This course will provide students with an opportunity to develop the Graduate Attributes specified below:

Critically competent in a core academic discipline of their award

Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.

Employable, innovative and enterprising

Students will develop key skills and attributes sought by employers that can be used in a range of applications.

Biculturally competent and confident

Students will be aware of and understand the nature of biculturalism in Aotearoa New Zealand, and its relevance to their area of study and/or their degree.

Globally aware

Students will comprehend the influence of global conditions on their discipline and will be competent in engaging with global and multi-cultural contexts.

Prerequisites

1. MATH101, or
2. NCEA 14 Credits at level 3 Mathematics, or
3. Cambridge: D at A level or an A at AS level in Mathematics, or
4. IB: 4 at HL or 5 at SL in Mathematics, or
5. Approval of the Head of School based on alternative prior learning.

Restrictions

Timetable 2024

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Tuesday 13:00 - 14:00 Ernest Rutherford 140
15 Jul - 25 Aug
9 Sep - 20 Oct
Lecture B
Activity Day Time Location Weeks
01 Monday 08:00 - 09:00 Rehua 102
15 Jul - 25 Aug
9 Sep - 20 Oct
Lecture C
Activity Day Time Location Weeks
01 Thursday 14:00 - 15:00 E16 Lecture Theatre
15 Jul - 25 Aug
9 Sep - 20 Oct
Lecture D
Activity Day Time Location Weeks
01 Friday 11:00 - 12:00 E16 Lecture Theatre
15 Jul - 25 Aug
9 Sep - 20 Oct
Tutorial A
Activity Day Time Location Weeks
01 Tuesday 10:00 - 11:00 Jack Erskine 038 Lab 4
15 Jul - 25 Aug
9 Sep - 20 Oct
02 Tuesday 14:00 - 15:00 Jack Erskine 038 Lab 4
15 Jul - 25 Aug
9 Sep - 20 Oct
03 Thursday 11:00 - 12:00 Jack Erskine 038 Lab 4
15 Jul - 25 Aug
9 Sep - 20 Oct
04 Friday 12:00 - 13:00 Jack Erskine 033 Lab 1
15 Jul - 25 Aug
9 Sep - 20 Oct

Course Coordinator

John Holmes

Lecturers

Fabian Dunker and Peyman Zawar-Reza

Assessment

Assessment Due Date Percentage  Description
Assignments 60% 10 Assignments, worth 6 % each (60 % total)
Final Exam 40%

Indicative Fees

Domestic fee $978.00

International fee $4,988.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Mathematics and Statistics .

All DATA101 Occurrences

  • DATA101-24S2 (C) Semester Two 2024
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