MPA in Data Science for Public Policy
Programme Code: TMPPDS
Department: School of Public Policy
For students starting this programme of study in 2023/24
Guidelines for interpreting programme regulations
Course code, title (unit value) |
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Before Year 1 |
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Introductory course |
PP407 Pre-Sessional Coding and Mathematics Bootcamp (0.0) |
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Year 1 |
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Paper 1 |
PP440 Micro and Macro Economics (for Public Policy) (1.0) |
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Or Upon satisfactorily demonstrating prior knowledge of Micro and Macro Economics, students may be exempted from PP440 and will be free to take an additional unit of option course subject to the approval of the Programme Director. |
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Paper 2 |
PP478 Political Science for Public Policy (1.0) |
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Paper 3 |
PP455 Quantitative Approaches and Policy Analysis (1.0) |
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Paper 4 |
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Year 2 |
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Paper 5 |
PP4B5 Capstone Project: MPA - Data Science for Public Policy (1.0) |
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Paper 6 |
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Paper 7 |
1.0 or 1.5 unit(s) from Public Policy: PP406 Philosophy for Public Policy (0.5) |
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PP411A Political Entrepreneurship (0.5) (suspended 2026/27) |
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PP411W Political Economy Applications for Public Policy (0.5) # |
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PP412 Cold War II? Public Policy Implications of US-China Relations in the 2020s (0.5) (suspended 2026/27) |
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PP413 Growth Diagnostics in Development: Theory and Practice (0.5) # |
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PP414 Policy-Making: Process, Challenges and Outcomes (0.5) |
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PP414W Policy-Making: Process, Challenges and Outcomes (0.5) (withdrawn 2026/27) |
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PP417A The Practice of Effective Climate Policy (0.5) (suspended 2026/27) |
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PP417W Economic Principles of Climate Change (0.5) |
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PP419 Advanced Empirical Methods for Policy Analysis (0.5) # |
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PP423 Anticipatory Policymaking (0.5) (suspended 2026/27) |
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PP424 Happiness and Public Policy (0.5) (suspended 2026/27) |
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PP425 Strategic Policymaking: Economic Analysis, Narrative Development, Political Feasibility, and Implementation (0.5) |
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PP426 Public Policy for Blockchains and Digital Assets (0.5) # |
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PP431 Reimagining Capitalism (0.5) (suspended 2026/27) |
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PP432 International policymaking, diplomacy and security (0.5) |
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PP433 Topics in Model Based Quantitative Analysis for Public Policy (0.5) # |
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PP434 Automated Data Visualisation for Policymaking (0.5) |
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PP448 International Political Economy and Development (0.5) |
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PP449 Comparative Political Economy and Development (0.5) (suspended 2026/27) |
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PP450 Public Organisations: Theory and Practice (0.5) # (suspended 2026/27) |
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PP452 Applying Behavioural Economics for Social Impact: Design, Delivery, Evaluation and Policy (0.5) # (suspended 2026/27) |
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PP465 City-Making: the Politics of Urban Form (0.5) |
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PP4E5 Innovations in the governance of public services delivery (0.5) |
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PP4G3 Designing and Managing Change in the Public Sector (0.5) (suspended 2026/27) |
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PP4J2 New Institutions of Public Policy: Strategic Philanthropy, Impact Investment and Social Enterprise (0.5) |
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PP4J4 Designing and Implementing Evidence-Informed Policies and Programmes (0.5) (withdrawn 2026/27) |
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PP4J5 Fiscal Governance and Budgeting (0.5) |
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PP4X6 Welfare Analysis and Measurement (1.0) (suspended 2026/27) |
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Paper 8 |
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1.0 or 1.5 unit(s) from Data Sciences: |
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HP434 Methods and Data for Health Systems Performance Assessment (0.5) |
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MY459 Computational Text Analysis and Large Language Models (0.5) # |
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MY461 Social Network Analysis (0.5) (suspended 2026/27) |
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MY472 Data for Data Scientists (0.5) |
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Footnotes
# means there may be prerequisites for this course. Please view the course guide for more information.
A: Paper 8, MY459: MY459: if instructor accepts a year of Econometrics and Data Science for Public Policy as pre-requisites.
B: Paper 8: MY459, MY461 and ST454 require knowledge of R
SUPPLEMENTARY CRITERIA FOR PROGRESSION FROM THE FIRST TO THE SECOND YEAR OF THE MPA in Data Science for Public Policy
- Students who attain at least a Pass grade in each of the first-year courses will be eligible to proceed into the second-year of the MPA in Data Science for Public Policy.
- A student on the MPA in Data Science for Public Policy programme who has attained a Fail grade in courses to the value of 1.0 unit and at least a Pass grade in the remaining courses to the value of 3.0 units will be eligible to proceed into the second year.
- A student who receives a Bad Fail in any course or who otherwise fails to meet the above criteria for progression will not be able to progress to the second year of the MPA in Data Science for Public Policy programme and will be entitled to repeat the failed courses as follows:
A student shall normally be entitled to repeat any failed courses only (on one occasion) and at the next normal opportunity, in accordance with paragraph 33 of the General Academic Regulations. The Repeat Teaching Panel may consider an application for repeat tuition in any failed courses from a student. Results obtained following a repeated attempt at assessment shall bear their normal value.
A student who has completed year one and is unable to complete year two of the MPA in Data Science for Public Policy programme will not receive an interim award.
Note for prospective students:
For changes to graduate course and programme information for the next academic session, please see the graduate summary page for prospective students. Changes to course and programme information for future academic sessions can be found on the graduate summary page for future students.