Quantitative Data Science - MATHE13959
Stream Summary
Faculty: SCI - Faculty of Science
School: Faculty of Science
Contact: http://www.maths.unsw.edu.au/
Program: 3959 - Data Science and Decisions
Award(s):
Bachelor of Data Science and Decisions (Major)
View stream information for previous years
Stream Outline
Quantitative Data Science is the study of methods for organising, modelling and analysing large and complex data relevant for businesses, governments or other organisations. The information gleaned from the data analysis is intended to improve business decisions and inform policies.
The program provides a strong technical background in mathematics, statistics, computer science and economics. The Quantitative Data Science major enables a student to specialise further in mathematical and statistical methods to interpret, understand and predict data.
The program and this major open a pathway to exciting careers in data science and data analytics.
The program provides a strong technical background in mathematics, statistics, computer science and economics. The Quantitative Data Science major enables a student to specialise further in mathematical and statistical methods to interpret, understand and predict data.
The program and this major open a pathway to exciting careers in data science and data analytics.
Stream Structure
A major in Quantitative Data Science consists of 66 units of credit as follows:-
Core Courses
Stage 1
Core Courses
Stage 1
- MATH1131 Mathematics 1A (6 UOC) or MATH1141 Higher Mathematics 1A (6 UOC)
- MATH1231 Mathematics 1B (6 UOC) or MATH1241 Higher Mathematics 1B (6 UOC)
Stage 2
- MATH2801 Theory of Statistics (6 UOC) or MATH2901 Higher Theory of Statistics (6 UOC)
- MATH2831 Linear Models (6 UOC) or MATH2931 Higher Linear Models (6 UOC)
- MATH2871 Data Management for Statistical Analysis (6 UOC)
Stage 3
- MATH3821 Statistical Modelling and Computing (6 UOC)
- MATH3871 Bayesian Inference and Computation (6 UOC)
Elective courses
Students must take 24 UOC from the following list:
Students must take 24 UOC from the following list:
- ACTL3141 Actuarial Models & Statistics (6 UOC)
- ACTL3142 Actuarial Data and Analysis (6 UOC)
- COMP2041 Software Construction (6 UOC)
- COMP2911 Eng. Design in Computing (6 UOC)
- COMP3121 Algorithms & Programming Tech (6 UOC)
- COMP3411 Artificial Intelligence (6 UOC)
- COMP3441 Security Engineering (6 UOC)
- COMP4121 Advanced & Parallel Algorithms (6 UOC)
- COMP4418 Knowledge Representation (6 UOC)
- COMP6771 Advanced C++ Programming (6 UOC)
- COMP9313 Big Data Management (6 UOC)
- COMP9315 Database Systems Implementat'n (6 UOC)
- COMP9318 Data Warehousing & Data Mining (6 UOC)
- COMP9417 Machine Learning & Data Mining (6 UOC)
- COMP9418 Advanced Machine Learning (6 UOC)
- ECON1102 Macroeconomics 1 (6 UOC)
- ECON2101 Microeconomics 2 (6 UOC)
- ECON2104 Applied Macroeconomics (6 UOC)
- ECON2111 Intro to Economic Development (6 UOC)
- ECON2206 Introductory Econometrics (6 UOC)
- ECON2209 Business Forecasting (6 UOC)
- ECON3107 Economics of Finance (6 UOC)
- ECON3123 Organisational Economics (6 UOC)
- ECON3130 Real Estate Economics (6 UOC)
- ECON3206 Financial Econometrics (6 UOC)
- ECON3208 Applied Econometric Methods (6 UOC)
- INFS1602 Digital Transformation in Bus (6 UOC)
- INFS3603 Intro to Business Analytics (6 UOC)
- MARK1012 Marketing Fundamentals (6 UOC)
- MARK3054 Marketing Analytics (6 UOC)
- MARK3085 Digital Mktg & Web Analytics (6 UOC)
- MATH1081 Discrete Mathematics (6 UOC)
- MATH2011 Several Variable Calculus (6 UOC)
- MATH2111 Higher Several Variable Calc (6 UOC)
- MATH3041 Mathematical Modelling (6 UOC)
- MATH3161 Optimization (6 UOC)
- MATH3411 Information, Codes and Ciphers (6 UOC)
- MATH5836 Data Mining (6 UOC)
Students enrolled in program 3959 (Data Science) will already complete MATH1131 or MATH1141, MATH1231 or MATH1241 and MATH2801 or MATH2901 as part of the core requirements for their program.
All COMP electives and electives listed below have prerequisite requirements. Prerequisite requirements may be completed as part of the core requirements for 3959 Data Science or by using free electives.
Additional electives requiring prerequisites are:
All COMP electives and electives listed below have prerequisite requirements. Prerequisite requirements may be completed as part of the core requirements for 3959 Data Science or by using free electives.
Additional electives requiring prerequisites are:
- ECON1102 Macroeconomics 1 (6 UOC)
- ECON2101 Microeconomics 2 (6 UOC)
- ECON2104 Applied Macroeconomics (6 UOC)
- ECON2111 Intro to Economic Development (6 UOC)
- ECON3107 Economics of Finance (6 UOC)
- ECON3123 Organisational Economics (6 UOC)
- ECON3130 Real Estate Economics (6 UOC)
Further Information
Please note that these requirements may be subject to change.
Students are advised to follow requirements according to the year they commenced. Please refer to previous editions of the Online Handbook for your program requirements.
Please note that these requirements may be subject to change.
Students are advised to follow requirements according to the year they commenced. Please refer to previous editions of the Online Handbook for your program requirements.
