Social Data Science MSc

Program Overview

The MSc Social Data Science program equips students with the skills to apply data analysis techniques to policy-related questions and develop evidence-based decision-making abilities. Delivered by the Q-Step Centre for Applied Data Analysis, the program offers specialization within policy subfields and emphasizes understanding complex political and cultural issues. Graduates are prepared for careers in policymaking, data science, and research, leveraging their data analysis skills, policy expertise, and critical thinking abilities.

Program Outline

Degree Overview:

• Objectives: The MSc Social Data Science program aims to equip students with the skills to apply data analysis techniques to policy-related questions and develop evidence-based decision-making abilities.
• Description: The program offers specialization within policy subfields like social and family policy, economic and public policy, environment, criminal justice, and security.
It is delivered by the Q-Step Centre for Applied Data Analysis, providing essential mathematical and programming skills for data acquisition and analysis. Students can gain practical experience through optional work placements or industry-based research consultancy projects. The program emphasizes understanding complex political and cultural issues in dynamic environments, relevant for both business and public sector careers or PhD study.

Outline:

• Content: The program explores the politics of policymaking, evidence-based decision-making, data analysis applications at various policy and decision-making stages, and the social complexities of policymaking.
• Structure: The program includes compulsory modules covering data analysis techniques and their application to policymaking.
Students gain technical understanding of social data science methods and practical software and programming skills to implement these methods for research questions.
• Modules:
• Optional Modules: Students can further enhance their employability skills by undertaking either a work placement or industry-based research consultancy project.
• Course Schedule: The program is offered as a 1-year full-time or 2-year part-time program.

Assessment:

• Methods: The program utilizes a variety of assessment methods, including:
• Assignments:
Essays, presentations, and group work are used to assess understanding and application of concepts.
• Dissertation/Research Consultancy Project: This is a major component of the program, allowing students to apply their skills to a policy-related topic of their own interest.
• Data Visualization: Students develop skills in communicating their findings to various audiences using effective data visualization tools.
• Criteria: Assessment criteria are likely to include:
• Understanding of concepts:
Demonstrating a thorough grasp of the theoretical and practical aspects of social data science and its application to policymaking.
• Analytical skills: Ability to analyze data, draw conclusions, and present findings effectively.
• Research skills: Ability to conduct independent research, design studies, and interpret results.
• Communication skills: Ability to communicate findings clearly and effectively in written and oral formats.

Teaching:

• Methods: The program utilizes a variety of teaching methods, including:
• Lectures:
Provide foundational knowledge and theoretical frameworks.
• Seminars: Facilitate discussion, critical thinking, and application of concepts.
• Presentations: Allow students to present their work and receive feedback.
• Group work: Encourages collaboration and teamwork.
• Reading and essay assignments: Promote independent learning and critical analysis.
• Faculty: The program is taught by experienced faculty members with expertise in social data science, policy analysis, and quantitative methods.
• Unique Approaches:
• Applied Data Analysis Workshops: These workshops provide further support to students interested in quantitative methods for the social sciences.
• Q-Step Seminar Series: This annual postgraduate conference brings together researchers from across humanities and social science disciplines.

Careers:

• Potential Career Paths: Graduates of the MSc Social Data Science program are well-prepared for careers in:
• Policymaking:
Working in government agencies, think tanks, or non-profit organizations.
• Data Science: Working in data-driven industries, such as technology, finance, or healthcare.
• Research: Pursuing PhD studies or working as research analysts.
• Opportunities: The program provides students with the skills and knowledge to pursue a wide range of career opportunities in both the public and private sectors.
• Outcomes: Graduates of the program are highly sought after by employers who value their data analysis skills, policy expertise, and critical thinking abilities.

Other:

• Employability Focus: The program emphasizes developing skills valued in professional and managerial careers, including research, analysis, communication, and critical thinking.
• Graduate Careers: The program has a strong track record of graduates securing successful career opportunities and progressing to PhD level study.
• Work Placement: The program offers optional work placements to provide students with hands-on experience in data analysis.
• Industry-Based Research Consultancy Project: This option allows students to partner with external organizations to examine research questions of mutual interest, integrating applied learning with direct workplace experience.

2024/25 entry UK fees per year: £12,000 full-time; £6,000 part-time International fees per year: £24,300 full-time; £12,150 part-time