MATH 2009 Introduction to Data Science

Credit Points 10

Legacy Code 301033

Coordinator Liwan Liyanage Opens in new window

Description Analysis of data is essential for scientific investigation, modelling processes and predicting future events. Data Science is the investigation of the tools required that allow us to perform this modelling and prediction. The increase in accessible data over the past few decades has promoted the use of Data Science, making it a desired skill in many professions. In this unit we further investigate the methods of regression, clustering and classification that form the basis of a data scientist's toolbox.

School Computer, Data & Math Sciences

Student Contribution Band HECS Band 2 10cp

Check your HECS Band contribution amount via the Fees page.

Level Undergraduate Level 2 subject

Pre-requisite(s) For students NOT enrolled in 3769 Bachelor of Data Science or 3770 Bachelor of Applied Data Science - MATH 1028 Statistical Decision Making or MATH 1003 Biometry or MATH 1030 Statistics for Business

Co-requisite(s) For students enrolled in 3769 Bachelor of Data Science or 3770 Bachelor of Applied Data Science - MATH 1033 Thinking About Data

Assumed Knowledge

Computer Programming.

Assessment

The following table summarises the standard assessment tasks for this subject. Please note this is a guide only. Assessment tasks are regularly updated, where there is a difference your Learning Guide takes precedence.

Item Length Percent Threshold Individual/Group Task
Online Quizzes 10 min per quiz 20 N Individual
Assignment 1 to consist of 10 or so pages of text, not including code and output 30 N Individual
Oral exam 15 min per student 10 Y Individual
Assignment 2 to consist of 10 or so pages of text, not including code and output 40 N Individual

Teaching Periods

2022 Trimester 1

Sydney City

Day

Subject Contact Antoinette Cevenini Opens in new window

View timetable Opens in new window