MSc Data Science (Social Analytics) / Course details
Year of entry: 2023
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The range of pathways reflects the interdisciplinary nature of the course and we welcome applications from students with backgrounds in a range of disciplines, including:
- Business and Management;
- Health Science;
- Social Sciences;
- Computer Science;
We provide training in core data science skills, embedded in a disciplinary context provided by the pathway, you will develop:
- computational skills;
- data analytical skills;
- data stewardship skills and knowledge;
- project design skills.
This innovative MSc in Data Science course is an opportunity for graduates from a broad range of disciplines to develop data science skills. Our goal is to help you develop into an agile, skilled data scientist, adept at working in variety of settings and able to meet the challenges and reap the rewards of interdisciplinary teamwork.
Teaching and learning
Teaching and Learning use multiple modes, including:
- Practical exercise
- Individual and teamwork
- Student presentations
Course unit details
Through a set of core units, you will develop a set of key data science skills.
The core units are:
- Machine Learning and Statistics (both semesters);
- Understanding Databases;
- Understanding Data and their Environment;
- Applications in Data Science.
Course unit list
The course unit details given below are subject to change, and are the latest example of the curriculum available on this course of study.
|Statistics and Machine Learning 1: Statistical Foundations||DATA70121||15||Mandatory|
|Statistics & Machine Learning 2: AI, Complex Data, Computationally Intensive Statistics||DATA70132||15||Mandatory|
|Applying Data Science||DATA70202||15||Mandatory|
|Understanding Data and their Environment||DATA71011||15||Mandatory|
|Programming in Python for Business Analytics||BMAN73701||15||Optional|
|Digital Planning - Spatial and Policy Analysis||PLAN60761||15||Optional|
|Survey Research Methods||SOST60421||15||Optional|
|Complex Survey Designs and Analysis||SOST70032||15||Optional|
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