Course Catalog

The course provides students with both theoretical and practical training in good database design. By the end of the course students will create a conceptual data model using entity-relationship diagrams, understand the importance of referential integrity and how to enforce data integrity constraints when creating a database. Students will be proficient in writing basic queries in the structured query language (SQL) and have a general understanding of relational database theory including normalization. 

This course examines the strategies, practices, and technologies of electronic government. Governments worldwide are integrating computer-based technologies into the centerfold of public administrative reforms to digitize the delivery of services and the process of governing. E-Government relies on information technology (IT) to automate and transform the processes to service citizens, businesses, governments, and other constituents. The course focuses on understanding models of delivering services through IT-enabled processes, open government, security issues, technologies, and economic evaluation. The course will feature emerging topics on Smart Cities and Internet of Things and the development of next generation broadband Internet networks. Lessons learned in the course can be applied to public organizations, nonprofit organizations, and civil society.

The course will examine the current state of global health informatics from both a local and global perspective, including opportunities and challenges. Focus will be placed on the transition from paper-based records to electronic systems, with a particular emphasis on large international open-source initiatives and the use of mobile devices. Guest speakers will share their experiences with WHO, cell phone based education, and regulatory issues. No programming or statistical experience is required.

This course introduces geographic information systems in the broader context of information management in business, government, and civil society. It highlights the importance of location and information about location across these realms. In addition to substantial hands-on work with traditional geographic information systems software, the course will provide exposure to other systems of people, processes, hardware, and software for collecting, managing, analyzing, and visualizing information about locations on the surface of the earth.

This course will explore informal learning as it occurs in a variety of contexts, including libraries, museums & makerspaces. After a brief review of existing literature on the spectrum of formal, semi-formal & informal learning, students will spend time working on prompts from partner organizations from the local community to reflect on their own learning process, evaluate curriculum, develop lesson plans & compare models of assessment that intersect w/social science research methods. Furthermore, the course will draw upon scholarship in fields related to User Experience & Interaction Design. Participants will be taught to make digital & physical mockups for use in areas such as application development, the design of technology learning spaces, workshop models or interactive museum exhibits. Our focus will be less on reading/writing & more on deliverables recognized in related education-oriented fields like multi-media reports, online tutorials & live presentations or instruction.

This course will provide a comprehensive review of information security concepts and industry best practices, covering the 8 domains of the CISSP Common Body of Knowledge: Security and Risk Management, Asset Security, Security Engineering, Communications and Network Security, Identity and Access Management Security Assessment and Testing, Security Operations, Software Development Security. Students will be prepared to take and pass the CISSP exam at their own expense upon completion of this course.

Introduces students to a range of rapid prototyping techniques and methods to analyze needs, opportunities and design spaces. Students will work in teams to develop ideas for novel computational devices or applications to meet identified needs. Covers the interlinked entrepreneurial skills of identifying an unmet need, exploiting technological opportunities, exploring a design space to refine an idea, and communicating a design vision through demonstrations with prototypes and proofs of concept. This enables developers to show how their envisaged working interactive technology will be used productively in a particular real-life context. Communicating the vision of computational devices is a challenge because dynamic use in context is hard for people other than the device's developers to imagine. The ability to produce convincing, clear, powerful demonstrations even at the early stages of a project is a highly valuable entrepreneurial skill, and also highly applicable within an organization. Directed and supervised investigation of selected topics in information studies that may include among others the social, political, and historical contexts of information creation and dissemination; computers and culture; information policy; community information systems; production, retrieval and evaluation of knowledge; computer-mediated communication.

In this immersive and experiential course, students consider "playfulness" as a key aspect of design methodologies and practices. Looking closely at the philosophical, social, and relational dynamics of play from multiple disciplinary angles, students will explore how playful approaches to design thinking and other design methodologies can encourage collaboration, engagement, and emergent, transformative solutions to a range of challenges that face us in our rapidly-changing, information-based culture.  The course aims to build student competency in design methods through a sequence of project experiences arising from a deep consideration of play.

This course will build a practical foundation for data science by teaching students basic tools and techniques that can scale to large computational systems and massive data sets. Students will first learn how to work at a Unix command prompt before learning about source code control software like git and the GitHub site. Next, the Python programming language will be covered, with a focus on specific aspects of the language and associated Python modules that are relevant for Data Science. Python will be introduced and used primarily via the IPython (or Jupyter) Notebooks, and will cover the Numpy, Scipy, MatPlotlib, Pandas, Seaborn, and scikit_learn Python modules. These capabilities will be demonstrated through simple data science tasks such as obtaining data, cleaning data, visualizing data, and basic data analysis.

This course will introduce advanced data science concepts by building on the foundational concepts presented in IS 490RB - Foundations of Data Science. Students will first learn how to perform more statistical data exploration and constructing and evaluating statistical models. Next, students will learn machine learning techniques including supervised and unsupervised learning, dimensional reduction, and cluster finding. An emphasis will be placed on the practical application of these techniques to high-dimensional numerical data, time series data, image data, and text data. Finally, students will learn to use relational databases and cloud computing software components such as Hadoop, Spark, and NoSQL data stores. Students must have access to a fairly modern computer, ideally that supports hardware virtualization, on which they can install software.