MSc Data Science (Social Analytics) / Course details

Year of entry: 2020

Course description

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;
  • geography;
  • planning;
  • computer science; and
  • mathematics.

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; and
  • project design skills.

Aims

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 team work.

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;
  • geography;
  • planning;
  • computer science; and
  • mathematics.

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; and
  • project design skills.

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.

There are five pathways through the course:

  • Applied Urban Analytics;
  • Computer Science Data Informatics;
  • Management and Business;
  • Mathematics;
  • Social Analytics.

Each pathway has a defined set of electives and dissertation options.

You are expected to have a degree with a substantial proportion of social science content; as a minimum you should have completed two degree level courses on topics from any of the following: sociology, psychology, anthropology, economics, history, human geography, political science, public health.

The following includes other skills/experience that would increase the chances of being selected:

  • evidence of applying statistical modelling to social sciences;
  • non-academic experience with the application of statistical models to social issues;
  • experience working on public policy issues or similar.

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.

TitleCodeCredit ratingMandatory/optional
Applied Spatial Analysis for Planning PLAN60761 15 Optional
Survey Research Methods SOST60421 15 Optional
Longitudinal Data Analysis SOST70022 15 Optional
Complex Survey Designs and Analysis SOST70032 15 Optional
Structural Equation and Latent Variable Modelling SOST70042 15 Optional
Multilevel Modelling SOST70292 15 Optional
Social Network Analysis SOST71032 15 Optional

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: dass@manchester.ac.uk