QTM3675 Probability for Risk Management

4 CreditsThe fundamental objective of this course is to prepare students for the successful completion of the first level probability examination (Exam P) of the Society of Actuaries. While the necessary theory is addressed, this course focuses on problem solving, so it is well suited for any student with an interest in applied probability concepts and how they are related to a wide variety of situations within and beyond actuarial science, finance, and economics. Topics include general probability and univariate and multivariate probability distributions.

Prerequisites: QTM1010 or AQM 2000

  • Program: Undergraduate
  • Division: Mathematics Analytics Science and Technology
  • Level: Advanced Elective (UGrad),Advanced Liberal Arts (UGrad)
  • Course Number: QTM3675
  • Number of Credits: 4

OIM3640 Problem Solving & Software Design
4 Advanced Liberal Arts Credits

Students who took this as MIS3640 cannot take this course

Teaches students assorted techniques and strategies to identify, approach and solve problems in business and personal areas. Students learn how to write computer programs to offer efficient solutions for certain types of problems using a computer programming language of the instructor's choice (currently Python). Students complete a capstone project to demonstrate their learning, create something of value, and add to their personal portfolio. This course emphasizes hands-on computer skill development in a computer lab setting. The examples and problems used in this course are drawn from diverse areas such as text processing, webpage scraping, web development and data analytics.

Prerequisites: (QTM1000 or AQM1000) and (SME2012 or OIM2000)

Students are expected to be able to open command prompt window or terminal window, edit a text file, download and install software, and understand basic programming concepts.

  • Program: Undergraduate
  • Division: Operations and Information Management
  • Level: Advanced Elective (UGrad),Advanced Liberal Arts (UGrad)
  • Course Number: OIM3640
  • Number of Credits: 4

OIM7555 Product Design and Development
(Formerly MOB7555)
3 Elective Credits

If you took and passed MOB7555, you cannot register for OIM7555, as these two courses are equivalent

Product Design and Development (PDD) is an integrated management course that provides students with a field-based understanding of the fundamentals of conceiving, evaluating, and developing successful new physical products. One works in a team-based environment learning how to translate a new product idea into a product concept and final design. The course extends the design toolkit introduced in core MBA courses, preparing students to create final working prototypes to be used to pursue funding for venture launch.

Weissman Foundry resources are used extensively to develop product prototypes. Student teams propose projects or are matched with projects in collaboration with participating client companies. The course culminates in the MBA Product Design Fair where teams present final product prototypes.

The course covers emerging topics and tools in sustainable product design as well as the use of generative artificial intelligence in the design process. While there is some case-based learning, the primary focus is on experiential learning through creating new products. The course is particularly relevant for students interested in launching ventures based on physical products, those seeking employment in companies with a product focus, those wishing to learn more about the design and innovation process through engaging in a semester-long development project, and those interested in product management roles.

(3.0 Credit Hours)

This course is typically offered in the following semesters: Spring

Prerequisites: None

  • Program: Graduate
  • Division: Operations and Information Management
  • Level: Graduate Elective (Grad)
  • Course Number: OIM7555
  • Number of Credits: 3

OIM6301 Programming for Business Analytics
(Formerly MIS6300)
3 Credits

If you took and passed MIS6300, you cannot register for OIM6301, as these two courses are equivalent

This course will introduce fundamental programming concepts including data structures and networked application program interfaces, using three different programming languages: SQL and Python. In addition, you will learn to manage structured data (SQL) and unstructured data (Python) At the end of this course, you will gain the basic understanding of programming and managing data in a data science driven world.

You will also learn:

· Understand multiple definitions of business intelligence and its relationship to analytics

· Understand how companies employ BI to shape strategy, monitor performance, and achieve competitive advantage

· Be able to identify opportunities for using different business analytical skills in a variety of business cases

· Understand database management and data warehousing and become competent in implementing them

· Learn to gather, analyze, summarize and visualize data to solve basic business problems

· Be able to program with SQL and Python

· Understand the challenges of big data and the technologies used to build models on and draw inferences from large data sets

Prerequisites: Admission in to the MSBA program. CAM students should contact Graduate Academic Services to pursue enrollment in this course. MBA students will be required to review approximately 2 hours of pre-work videos.

  • Program: Graduate
  • Division: Operations and Information Management
  • Level: MSBA Core (Grad),Graduate Elective (Grad)
  • Course Number: OIM6301
  • Number of Credits: 3

QTM2623 Programming with R for Business Analytics
4 Credits
This 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

  • Program: Undergraduate
  • Division: Mathematics Analytics Science and Technology
  • Level: Advanced Elective (UGrad),Advanced Liberal Arts (UGrad)
  • Course Number: QTM2623
  • Number of Credits: 4

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.

  • Program: Undergraduate
  • Division: Operations and Information Management
  • Level: Advanced Elective (UGrad),Advanced Management (UGrad)
  • Course Number: OIM3509
  • Number of Credits: 4

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

  • Program: Graduate
  • Division: Operations and Information Management
  • Level: MSAEL (Grad)
  • Course Number: OIM6601
  • Number of Credits: 3

LAW3601 Public International Law and World Order
4 Advanced Liberal Arts Elective Credits
This 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)

  • Program: Undergraduate
  • Division: Accounting and Law
  • Level: Advanced Elective (UGrad),Advanced Liberal Arts (UGrad)
  • Course Number: LAW3601
  • Number of Credits: 4

QTM1000 Quantitative Methods for Business Analytics I
4 Credits
The 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

  • Program: Undergraduate
  • Division: Mathematics Analytics Science and Technology
  • Level: Foundation Liberal Arts (UGrad)
  • Course Number: QTM1000
  • Number of Credits: 4

QTM1010 Quantitative Methods for Business Analytics II
4 Credits
This 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

  • Program: Undergraduate
  • Division: Mathematics Analytics Science and Technology
  • Level: Foundation Liberal Arts (UGrad)
  • Course Number: QTM1010
  • Number of Credits: 4