Build the rich perspective employers want.
Whether you want to acquire non-business knowledge to break into a new industry or fuse your newfound business skills with your undergraduate area of study, you’ll prepare for your career with the choice of an interdisciplinary elective.
You can choose graduate level coursework from four distinguished Northeastern University colleges:
- College of Arts, Media, & Design
- Khoury College of Computer Sciences
- College of Engineering
- College of Social Sciences & Humanities
Our corporate partners have told us that they seek managers with multidimensional backgrounds. These electives will ensure that you graduate with a well-rounded perspective, ready to approach business problems from multiple angles.
College of Arts, Media, and Design Courses
Offers an overview and introduction to leadership knowledge areas, tools, and skills sets for the arts and culture sector. Key topics include issues and challenges in the management of arts-oriented organizations, leadership characteristics and techniques for arts and culture teams, balancing organizational priorities with artistic vision and values, board formation and management, audience outreach, and operational practices. Focuses on the administration of people and processes to communicate mission; realize goals; and effectively manage the creative resources, human resources, and financial challenges of nonprofit arts and cultural organizations.
AACE 6000 | 3 credits
Examines the potential of interfaces as mediators between information and users. Explores iterative prototyping and research methods to analyze patterns of behavior and implications of interface on effective communication. Utilizes observation, empathy, ethnography, and participatory design methods to offer students an opportunity to increase their understanding of audiences’ and stakeholders’ motivations and expectations. Requires graduate standing or permission of program coordinator or instructor.
ARTG 6310 | 4 credits
Covers basic principles of print and digital design with lectures, skills training, and a maker’s workshop. Introduces students to the foundations of typography, color, grids, and use of images for storytelling. Students design, prototype, and produce a print magazine and website.
JRNL 5311 | 4 credits
Khoury College of Computer Sciences Courses
Introduces the fundamental problems, theories, and algorithms of the artificial intelligence field. Topics include heuristic search and game trees, knowledge representation using predicate calculus, automated deduction and its applications, problem solving and planning, and introduction to machine learning. Required course work includes the creation of working programs that solve problems, reason logically, and/or improve their own performance using techniques presented in the course. Requires experience in Java programming.
CS 5100 | 4 credits
Introduces relational database management systems as a class of software systems. Prepares students to be sophisticated users of database management systems. Covers design theory, query language, and performance/tuning issues. Topics include relational algebra, SQL, stored procedures, user-defined functions, cursors, embedded SQL programs, client-server interfaces, entity-relationship diagrams, normalization, B-trees, concurrency, transactions, database security, constraints, object-relational DBMSs, and specialized engines such as spatial, text, XML conversion, and time series. Includes exercises using a commercial relational or object-relational database management system.
CS 5200 | 4 credits
Discusses the practical issues and techniques for data importing, tidying, transforming, and modeling. Offers a gentle introduction to techniques for processing big data. Programming is a cross-cutting aspect of the course. Offers students an opportunity to gain experience with data science tools through short assignments. Course work includes a term project based on real-world data. Covers data management and processing—definition and background; data transformation; data import; data cleaning; data modeling; relational and analytic databases; basics of SQL; programming in R and/or Python; MapReduce fundamentals and distributed data management; data processing pipelines, connecting multiple data management and analysis components; interaction between the capabilities and requirements of data analysis methods (data structures, algorithms, memory requirements) and the choice of data storage and management tools; and repeatable and reproducible data analysis.
DS 5110 | 4 credits
Introduces the fundamental techniques of quantitative data analysis, ranging from foundational skills—such as data description and visualization, probability, and statistics—to the workhorse of data analysis and regression, to more advanced topics—such as machine learning and networks. Emphasizes real-world data and applications using the R statistical computing language. Analyzing and understanding complex data has become an essential component of numerous fields: business and economics, health and medicine, marketing, public policy, computer science, engineering, and many more. Offers students an opportunity to finish the course ready to apply a wide variety of analytic methods to data problems, present their results to nonexperts, and progress to more advanced course work delving into the many topics introduced here.
INSH 5301 | 4 credits
College of Engineering Courses
Seeks to develop in-depth knowledge and experience in prototyping by focusing on engineering processes and instrumentation that are used in different industries. Studies the prototyping cycle, from initial process flow and sketching to prototype development to testing and analysis, with an emphasis on iteration. Analyzes how different kinds of engineering prototypes can address design and user-interface needs vs. functional needs, such as looks-like and works-like prototypes. Offers students an opportunity to obtain operating knowledge of methods including 3D printing, SolidWorks, off-the-shelf hardware-software interfaces, simulation, embedded systems, product testing, prototype analysis, and prototype iteration.
GE 5030 | 4 credits
Focuses on the main processes needed to develop a complex, high-technology product. Emphasizes the most important techniques and approaches used in a startup environment. Seeks to benefit students of all engineering disciplines including computer science and biomedical, industrial, electrical, mechanical, computer, and chemical engineering. Includes a running practical project in which a new product is designed and executed through a series of small projects for each phase of the product development process. Topics include the product life cycle, new product development processes, project planning and management, new product idea generation, the systems approach to product development, design for manufacturing, market testing and launch, and escalation to manufacturing.
GE 5100 | 4 credits
Introduces data mining concepts and statistics/machine learning techniques for analyzing and discovering knowledge from large data sets that occur in engineering domains such as manufacturing, healthcare, sustainability, and energy. Topics include data reduction, data exploration, data visualization, concept description, mining association rules, classification, prediction, and clustering. Discusses data mining case studies that are drawn from manufacturing, retail, healthcare, biomedical, telecommunication, and other sectors.
IE 5640 | 4 credits
Offers students an opportunity to learn how to use visualization tools and techniques for data exploration, knowledge discovery, data storytelling, and decision making in engineering, healthcare operations, manufacturing, and related applications.Covers basics of Python and R for data mining and visualization. Introduces students to static and interactive visualization charts and techniques that reveal information, patterns, interactions, and comparisons by focusing on details such as color encoding, shape selection, spatial layout, and annotation.
IE 6600 | 4 credits
Offers topics of interest to the staff member conducting this class for advanced study. May be repeated without limit.
IE 7374 | 4 credits
Explores environmental and economic aspects of different materials used in products throughout the product life cycle. Introduces concepts of industrial ecology, life cycle analysis, and sustainable development. Students work in teams to analyze case studies of specific products fabricated using metals, ceramics, polymers, or paper. These case studies compare cost, energy, and resources used and emissions generated through the mining, refining, manufacture, use, and disposal stages of the product life cycle. Debates issues in legislation (extended product responsibility, recycling mandates, and ecolabeling) and in disposal strategies (landfill, incineration, reuse, and recycling). Discusses difficulties associated with environmental impact assessments and the development of decision analysis tools to weigh the tradeoffs in technical, economic, and environmental performance, and analyzes specific case studies.
ME 5645 | 4 credits
College of Social Sciences and Humanities Courses
Offers an intensive study of econometric techniques applied to cross-section, time-series, and panel data. Applies the fundamentals of econometrics to analyzing structural economic models, forecasting, and policy analysis. Computer applications and an empirical research project are an integral part of the course.
ECON 5140 | 4 credits
Examines how states, institutions, policy choices, and social forces shape—and are influenced by—the global economy and the world polity. Examines changes in relations among and between the countries of the Global North and the Global South. Draws on concepts, propositions, and theories from various disciplinary approaches to (international) political economy, as well as Marxian, world-systems, and feminist theories.
INTL 5200 | 4 credits
Offers a comprehensive overview of resource development and financial management in nonprofit organizations. Topics include fund-raising and development planning, nonprofit budgeting and financial reporting, investments and earned income for nonprofits, and government contracting and grants.
PPUA 6553 | 4 credits
Designed to familiarize master’s degree students with the essential ideas and methods of microeconomics and their application to a wide range of domestic public policy issues at the national, state, and local level. Emphasizes the role of program and management incentives in influencing behavior and policy outcomes. Focuses on understanding the ideas of microeconomic theory and applying them to a range of alternative public policy issues. Offers students an opportunity to develop a clear understanding of essential economic ideas and how the economic perspective can be applied to a wide range of public policy issues. Restricted to master’s degree students only.
LPSC 6313 | 4 credits
Introduces the systematic use of visualization techniques for supporting the discovery of new information as well as the effective presentation of known facts. Based on principles from art, graphic design, perceptual psychology, and rhetoric, offers students an opportunity to learn how to successfully choose appropriate visual languages for representing various kinds of data to support insights relevant to the user’s goals. Covers visual data mining techniques and algorithms for supporting the knowledge-discovery process; principles of visual perception and color theory for revealing patterns in data, semiotics, and the epistemology of visual representation; narrative strategies for communicating and presenting information and evidence; and the critical evaluation and critique of data visualizations. Requires proficiency in R.
INSH 5302 | 4 credits