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Program Evaluation and Data Analytics MS, Watts College of Public Service and Community Solutions
The MS in program evaluation and data analytics is an interdisciplinary and professional degree program that emphasizes skills needed to leverage data to improve organizational performance in the public, nonprofit and private sectors. It combines courses in program evaluation with data science classes that empower students to utilize a diverse array of tools to generate insights on social impact and leverage data in organizations.
Students receive training in data programming, visualization, dashboard design, open data, project management and impact analysis. Through this, students build the technical skills necessary to implement evidence-based approaches to policy and management.
Unlike other data science degrees, this program is built using public sector and nonprofit examples. Students do not need a background in computer programming before starting the degree. Through a project-based curriculum and individualized attention, students develop expertise in performance and evaluation frameworks. Graduates are prepared to work as policy analysts, managers, chief data officers or evaluation specialists.
For more information:
PAF 540 Advanced Policy Analysis, School of Public Affairs
Data and information are essential to public agencies and other organizations in supporting decisions about government policies and programs. One crucial set of skills for policy analysts and managers in this environment involves being able to collect, manage, and analyze significant amounts of data to evaluate the effectiveness of a program. This was the focus of PAF 502 and PAF 573. In this course, we examine additional ways that data management, visualization, and modeling skills can be used to provide insight and products useful to policy analysts and managers. A large part of the course focuses on data science techniques used to gain insights from so-called “big data,” including using machine learning to target messages and recommendations, detect outliers, and measure and predict public outcomes using social media. The course also introduces computational and social network models useful in understanding how to create contagions, identify influencers, and harness the wisdom of crowds. While familiarity with statistical modeling and computer programming will be helpful, no prior modeling or programming knowledge is required. A large amount of the data analysis and modeling will be done in spreadsheet software.
For more information about the Master of Public Policy (MPP) and Master of Public Administration (MPA) degrees:
PAF 582 E-Public Administration, School of Public Affairs
This course examines multiple aspects of information technology use in government and public administration. Far more than the administration of websites or online transactions, technology influences the way in which public organizations communicate, engage with citizens, collaborate with partners, and innovate in their communities. Technology has played a critical role in social and organizational change over the past few decades and is often viewed by elected officials and international organizations as a source of public sector reform. Yet, technology use is embedded in social processes and institutions, and must be understood in the context of larger issues in public administration, such as strategic management, governance, and democratic values. Beginning with a history and overview of goals for technology use, the course examines issues for digital inclusion, organizational and managerial considerations, information policy, citizen engagement through technology, and policy and governance for smart cities.
For more information about the Executive MPA Program (EMPA):