QTM2623 Programming with R for Business Analytics
4 CreditsThis course provides experience in developing, testing, and implementing business analytics software using the R language. R has become the leading tool for analytics software design, statistical computing, and graphics. The language is greatly enhanced by numerous open-source contributed packages and textbooks submitted by users, and it is used almost exclusively in most of the leading-edge analytics applications, such as statistical analysis and data mining. No prior programming experience is assumed. Students will become proficient in programming in the R language with datasets of all kinds with an emphasis on statistical exploration, data mining, graphics, and advanced programming concepts. The course will be case-oriented. The intent is to further enhance the learning experience from other analytics courses, such as QTM1010 and QTM2000.

Prerequisites: QTM1010 and QTM2000 or permission from the instructor

OIM3509 Project Management
(Formerly MOB3509)
4 General Credits

Students who took this as MOB3509 cannot register for this course

According to the Project Management Institute (PMI), there are nearly 250,000 open project management jobs each year across seven project-intensive industries: business services, construction, finance and insurance, information services, manufacturing, oil and gas, and utilities. As more work becomes project-based, projects grow in complexity, and clients demand accountability and efficiency, graduates with project management skills will be in increasingly high demand. In this course, you will learn critical skills for leading cross functional teams using up-to-date PM best practices, methodologies, and tools. This course is applicable across career paths such as consulting, information technology, entrepreneurship, new product development and many others. Students will be exposed to both the technical and behavioral skills required to effectively lead project teams -- whether as an official "Project Manager" or an unofficial leader temporarily charged with leading a project implementation. The course will be taught primarily via case study discussion, with a significant "hands-on" component that includes the authoring of key project plan documents and a solid exposure to Microsoft Project. At the conclusion of this course, students will have satisfied PMI's educational requirements to apply for the Certified Associate in Project Management (CAPM) exam. This course is an approved elective for the Operations Management concentration.

Prerequisites: (SME2001 or ACC2002) and (SME2002 or OIM2001) and (SME2011 or MKT2000) and SME2012 or OIM2000) or permission of the instructor.

OIM6601 Project Management Under Uncertainty
3 Credits (MSAEL Core)This course offers methods and frameworks for commercializing nascent technologies that offer potentially breakthrough value to the market and therefore, enormous reward for the firm, but whose value propositions and applications are highly uncertain at the outset. Aside from readings and cases, students' job will be to undertake a project either from their own organization or one provided by the faculty and, applying the tools and methods of the course, understand the technology, learn how to articulate it in terms of market opportunity, scope out the potential applications, and begin doing the hard work of evaluating the potential of the opportunity, incubating it and determining next steps.

Prerequisites: MOB6600 and EPS6600; OIM 6600

LAW3601 Public International Law and World Order
4 Advanced Liberal Arts Elective CreditsThis course considers public international law as a way of framing and understanding the larger world in which we live. We will consider foreign relations and the United Nations system, the implications of global interdependence, and an increasingly robust international judicial system. Does international law actually create global order, or does it merely reflect political order that exists in other settings? When should national sovereignty yield to the wider concerns of the global community? What role do non-state actors (multinational businesses, NGOs, advocacy groups) play in the global legal regime?

These questions (and many others) have been at the center of the quest to create order in a rapidly changing world where the pace of technological innovation, entrepreneurship, and the increasingly free movement of people, capital, and ideas often far outpace the capacity of any legal regime (domestic or international) to keep up. We will study these issues and related themes throughout the semester. Special emphasis is placed on understanding international institutions, human rights (including the intersection of human rights with global business), refugee law, the regulation of warfare (including "humanitarian" intervention and responses to global terrorism), international environmental law, transnational dispute settlement, and business ethics in the global setting.

Prerequisites: Foundation Law course, (LAW1000)

QTM1000 Quantitative Methods for Business Analytics I
4 CreditsThe course introduces the necessary core quantitative methods that are prerequisites to follow-on courses in QTM and in Babson's integrated core business offerings. Statistical software and the use of spreadsheets are integrated throughout so that students better comprehend the importance of using modern technological tools for effective model building and decision-making. About two thirds of the course is data-oriented, exposing students to basic statistical methods, their conceptual underpinning, such as variability and uncertainty, and their use in the real world. Topics include data collection, descriptive statistics, elementary probability rules and distributions, sampling distributions, and basic inference. The last third of the course is dedicated to selected non-statistical quantitative techniques applied to business models. Topics include curve fitting, differential calculus applications to non-linear optimization, and introduction to the time value of money.

Prerequisites: None

QTM1010 Quantitative Methods for Business Analytics II
4 CreditsThis course explores decision-making problems in a managerial context using algebraic, spreadsheet, graphical, and statistical models. The focus is on understanding basic mathematical and modeling principles through the analysis of real data. The course emphasizes communicating in-context interpretations of the results of analysis in written, visual, and oral form. A foundation in introductory statistics and use of spreadsheets is essential because these concepts are extended and reinforced throughout the course. Topics include introductions to linear regression, time series analysis, linear programming, decision analysis and simulation. It emphasizes the use of appropriate software and the latest technological methods for accessing and analyzing data.

Prerequisites: QTM1000 or AQM1000

QTM3605 Quantitative Analysis of Structural Injustice
4 Advanced Liberal Arts Credits

This course provides a survey of current quantitative methods for analyzing structural disparities. Using philosophies from interdisciplinary fields, we follow examples from education, housing, and other topics to document the direction and size of social and economic disparities. The course begins with a discussion on the philosophies of major data issues. We then learn to analyze disparities using a wide range of data types - spatial, panel, experimental, and observational - through the use of raw, real-world data sets. Discussions will center on biases resulting from data, models, and algorithms. The course uses R and QGIS. Prior to enrolling, students should have a foundation in regression analysis

Prerequisites: AQM 2000 OR QTM 2000

QTM3635 Quantitative Methods for Machine Learning
4 Advanced Liberal Arts CreditsThe ease of data collection coupled with plummeting data storage costs over the last decades have resulted in massive amounts of data that many business organizations have at their fingertips. Effective analysis of those data followed by sound decision-making is what makes a company an analytical competitor. This course is dedicated to learning and applying advanced quantitative tools for solving complex machine learning problems. The course will build on analytical tools learned during AQM 2000 (Predictive Business Analytics) course, introducing modern advanced tools ranging from random forests to support vector machines and artificial neural networks. Each topic covered in this course will be discussed in the context of wide-ranging real-world applications such as email spam prediction; handwritten digit recognition; topic modeling/text mining; etc. The implementation of the introduced topics will be carried out in R/RStudio.

Prerequisites: QTM2000 or AQM2000

HIS4620 Race and Ethnicity in Latin America
4 Advanced Liberal Arts Credits

What did it mean to be _Black_ or _Indian_ or _White_ in Latin America? What is mestizaje and indigenismo? What did it mean to be of mixed descent? What does these mean today? Is _race_ a means to political empowerment, or the source of discrimination? This seminar explores these issues and ideas in the context of colonial and postcolonial Latin American history. In answering these questions, we will look at a variety of theoretical and disciplinary approaches to _race._ Armed with the history of these changing ideas, we will then consider a variety of case studies from throughout Latin America.

Prerequisites: Any combination of 2 ILA (HSS, LTA, CSP, LVA, CVA)

MOB3585 Racial Identity and Racism at Work: a US Context
4 Advanced Management Credits

This course provides numerous opportunities to explore your personal and social identity. You will delve into materials that expose you to protagonists, contexts and issues from multiple racial and cultural perspectives. Further, you will engage in activities designed to help you become more culturally competent. This is a rare opportunity to learn about racial, ethnic and cultural diversity in connection with gaining great insight into your own identity. The course is designed in three phases; you will: 1) explore race and racism; 2) examine the convergence of life domains and lived racial experiences; and, 3) investigate how race and racism intersect with lived experiences to influence privilege/bias, authenticity and professionalism in the workplace.

COURSE OBJECTIVES

This course facilitates the accomplishment of several learning objectives, by increasing student capacity to:

1. Brainstorm, analyze and communicate key ideas to others, in written and oral formats.

2. Research and voice divergent perspectives on the same issue.

3. Explore personal and social identities, including surfacing possible blind spots and biases, and privileges as it relates to race, ethnicity and culture.

4. Analyze issues you might not often confront given the unique and diverse perspectives represented in the course.

5. Improve writing and public speaking skills while developing a competency to analyze divergent opinions and articulate opinions that are supported by fact.

Keywords: Race, Racism, Diversity, Identity, Intersectionality, Culture, Divergent viewpoints

Prerequisites: FME and FYS