Master of Data Science (Social Analytics)

Program Overview

The Master of Data Science (Social Analytics) program at Durham University combines data science and social science to equip students with the skills to analyze and solve social problems. This one-year program offers a conversion course for non-quantitative backgrounds and culminates in a research project applying learned skills to a social science domain. Graduates are prepared for data-driven careers in various sectors, addressing real-world challenges and improving lives.

Program Outline

Degree Overview:

Objectives:

• Equip students with advanced data science and AI skills to inform policy and business decisions.
• Provide students with social data knowledge and skills to improve people's lives.
• Offer a conversion course accessible to graduates with non-quantitative backgrounds.

Description:

• This 1-year full-time program focuses on the application of data science in social analytics.
• It combines core data science modules with specialized social science modules.
• Students gain the ability to access, clean, analyze, and visualize data to solve social problems.
• The program culminates in a research project applying learned skills to a social science domain.

Outline:

Course Structure:

• Modules:
• Introduction to Computer Science (optional)
• Introduction to Mathematics for Data Science (optional)
• Text Mining and Language Analytics (optional)
• Data Exploration, Visualisation and Unsupervised Learning (optional)
• Ethics and Bias in Data Analytics (optional)
• Strategic Leadership (optional)
• Machine Learning (optional)
• Computational Social Science (optional)
• Critical Perspectives in Data Science
• Social Science: Questions, Concepts, Theories and Methods
• Programming for Data Science
• Introduction to Statistics for Data Science
• Data Science Research Project
• Delivery: Lectures, seminars, workshops, computer classes, independent study, research, analysis, case studies, and structured reading.
• Assessment: Essays, online assessments, reports, individual and group presentations.

Course Schedule:

• The program starts in September 2024.
• It is a full-time, 1-year program.

Individual Modules:

• Critical Perspectives in Data Science: Develops ethical and contextual understanding of data analysis.
• Social Science: Questions, Concepts, Theories and Methods: Introduces key differences between social science and other disciplines and research methods.
• Programming for Data Science: Covers data gathering, manipulation, and processing using Python.
• Data Science Research Project: An in-depth research project in a social science domain.

Assessment:

• Combination of essays, online assessments, reports, and individual/group presentations.
• Research project as the culminating assessment.

Teaching:

• Interdisciplinary approach with modules from various departments.
• Varied teaching methods: lectures, seminars, workshops, computer classes.
• Research-driven modules with integrated research training.
• Encouragement to develop research skills and critical thinking.

Careers:

• Data-driven career opportunities in various sectors.
• Potential for stimulating and rewarding work improving lives in diverse fields.

Other:

• The program is designed for students with non-quantitative backgrounds.
• Entry requirements include a first or upper second class honors degree in any field.
• International students are welcome.

Conclusion:

The Master of Data Science (Social Analytics) program at Durham University provides a comprehensive and interdisciplinary approach to data science in the social domain. It equips graduates with the skills and knowledge to tackle real-world problems and contribute to positive societal change.

Full Time Fees

Tuition fees

Home students £13,500 per year EU students £31,500 per year Island students £13,500 per year International students £31,500 per year The tuition fees shown are for one complete academic year of full time study, are set according to the academic year of entry, and remain the same throughout the duration of the programme for that cohort (unless otherwise stated).