https://studiegids.vu.nl/en/courses/2025-2026/S_DSPGKnowledge and understanding – The student has acquired an understanding of:data science terminology, key considerations in working meaningfully with data, and of data science techniques;key issues in governance and public service delivery arising in relation to the use of data science techniques and predictive analytics;a foundational understanding of data science and applications across the public sector.Skills – The student has acquired the skills to:deploy applied statistical analysis in R and Python;analyse real-life problems in various policy sectors arising in relation to the use of data science and predictive analytics in government.Attitude – The student displays:a reflective and analytical attitude in relation to how data is utilized for societal impact and the challenges and trade-offs inherent in data-driven management and policy.As data-driven approaches become increasingly crucial to modern governance, public administrators are increasingly tasked with managing data-driven systems, including critically evaluating the data that underpin them. This means that, in addition to understanding key issues in governance and public service delivery, effective public leaders will also need to possess at least a foundational understanding of data science and applications across the public sector. This course provides both a theoretical foundation and hands-on technical training to prepare future public administrators and leaders for such roles. Students will explore how data science can promote good governance, ethical decision-making, and effective public service delivery while also critically evaluating questions around data governance, ethics, and public value creation. Using case studies from government and public service, globally, students will explore how data is utilized for societal impact and discuss the challenges and trade-offs inherent in data-driven management and policy. The course emphasizes practical skills through weekly data labs where students will gain proficiency in applied statistical analysis in R and Python. They will also explore advanced topics like natural language processing, machine learning, and predictive analytics, all within the context of real-world public sector applications.Lectures and study group sessions (labs)Data Mini-Projects, Written Assignments, Final Project/PortfolioTo be announced in course manual (see Canvas).In this course, you cannot enroll for one of the study groups yourself, but you will be assigned by the course coordinator. The allocation will be announced via Canvas. Please note: You do have to register for the course and the other course components on VU.nl.