Curriculum

Curriculum requirements

Attend an 18-hour compulsory summer boot camp

Before the commencement of the programme, all candidates must attend a mandatory 18-hour social data analytics boot camp. The boot camp training programme is designed to provide candidates with beginner-level skills in social data analytics so that they can follow the more advanced curriculum for the degree of Master of Social Sciences in the field of Social Data Analytics. The boot camp will be taught over three to four days, organised around the following topics:

Welcome to the Boot Camp in Social Data Analytics: pedagogical approach, how to get started; an introduction to open-source software R and Rstudio and how to customize your interface

Introductory/refresher course in algebra, probability and statistics

Using objects (e.g. vectors and dataframes) and different classes of objects (e.g. numeric vs. string) in R-Studio

How to clean, reshape, and restructure data with the tidyverse

Basic Programming: write functions, loops, and learn how to debug your code

Communicating and Collaborating with RMarkdown, Rpres, Shiny and Github

Students are required to complete 5 compulsory courses, 3 elective courses and 1 capstone project throughout their studies.

Before the commencement of the programme, all students must attend a mandatory 18-hour social data analytics summer boot camp. The boot camp training programme is designed to provide students with beginner-level skills in social data analytics so that they can follow the more advanced curriculum for the MSocSc(SDA) programme.

Compulsory courses
MSDA6001 Introduction to social data analytics
MSDA6002 Statistical foundations
MSDA6003 Machine learning
MSDA6004 Research design and inference in the social sciences
MSDA6005 Programme for social scientists

Two elective courses from the following list
MSDA7001 Big data solutions to social problems
MSDA7002 Simulating human behaviors with agent-based models
MSDA7003 Text as data: Natural language processing and social research
MSDA7004 Social network analysis
MSDA7005 Media data analysis

One elective course from the following list
GEOG7308 Machine learning for geospatial data
GEOG7310 Cloud computing for geospatial data analytics
GEOG7311 Web GIS
MSBH7005 Scientific inquiry and research methods in behavioral health
SOCI7006 Research methods in media, culture and creative cities
SOWK6185 Qualitative research methods

A capstone project
MSDA8001 Capstone project

Please click here for the regulations, syllabus and course descriptions.

Curriculum requirements

Duration and Tuition fee

1-year full-time

2-year part-time