{"id":1300,"date":"2023-12-12T06:32:43","date_gmt":"2023-12-12T06:32:43","guid":{"rendered":"https:\/\/www.socsc.hku.hk\/sda-uat\/?page_id=1300"},"modified":"2025-08-12T07:36:18","modified_gmt":"2025-08-12T07:36:18","slug":"curriculum","status":"publish","type":"page","link":"https:\/\/www.socsc.hku.hk\/sda\/curriculum\/","title":{"rendered":"Curriculum"},"content":{"rendered":"\t\t
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Programme Curriculum<\/h2>\n <\/div>\n \n \n \t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Attend an 18-hour compulsory summer boot camp<\/span>\n

\nBefore 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:

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  1. 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<\/li>\n
  2. Introductory\/refresher course in algebra, probability and statistics<\/li>\n
  3. Using objects (e.g. vectors and dataframes) and different classes of objects (e.g. numeric vs. string) in R-Studio<\/li>\n
  4. How to clean, reshape, and restructure data with the tidyverse <\/li>\n
  5. Basic Programming: write functions, loops, and learn how to debug your code<\/li>\n
  6. Communicating and Collaborating with RMarkdown, Rpres, Shiny and Github<\/li>\n\n<\/span>\n<\/ol>\n<\/p>\n <\/div>\n \n \n \t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    \nStudents are required to complete 5<\/strong> compulsory courses, 3<\/strong> elective courses and 1<\/strong> capstone project throughout their studies.

    \nBefore the commencement of the programme, all students must attend a mandatory 18-hour social data analytics summer boot camp<\/strong>. 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.\n

    \nCompulsory Courses<\/strong><\/span>
    \nMSDA7001 Introduction to social data analytics
    \nMSDA7002 Statistical foundations
    \nMSDA7003 Machine learning
    \nMSDA7004 Research design and inference in the social sciences
    \nMSDA7005 Programming for social scientists
    \n
    \nElective Courses<\/strong><\/span>
    \nAt least two elective courses from the following list*<\/span>
    \nMSDA7101 Big data solutions to social problems
    \nMSDA7102 Simulating human behaviours with agent-based models
    \nMSDA7103 Text as data: Natural language processing and social research
    \nMSDA7104 Social network analysis
    \nMSDA7105 Media data analysis
    \n
    \nOne additional elective course can also be taken from other programmes*<\/span>
    \nGEOG7308 Machine learning for geospatial data
    \nGEOG7310 Cloud computing for geospatial data analytics
    \nGEOG7311 Web GIS
    \nMSBH7005 Scientific inquiry and research methods in behavioral health
    \nSOCI7006 Research methods in media, culture and creative cities
    \nSOWK6185 Qualitative research methods
    \n
    \nCapstone project (Compulsory)<\/strong><\/span>
    \nMSDA8001 Capstone project
    \n
    \n\nPlease click here<\/a> for the regulations, syllabus and course descriptions.\n\n

    \n*Offering schedule and quota is subject to availability\n\n\n<\/span>\n\n<\/span>\n<\/ol><\/p>\n <\/div>\n \n \n \t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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    \n \n


    \nStudents are required to complete 5<\/strong> compulsory courses, 3<\/strong> elective courses and 1<\/strong> capstone project throughout their studies.

    \nBefore the commencement of the programme, all students must attend a mandatory social data analytics summer boot camp<\/strong>. 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.\n

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