Skip Navigation LinksHome / Academics / Academic Divisions / Math and Science / Course Listings

Math and Science Division Course Listings

Undergraduate

  1 2   

NST1010 - ASTRONOMY

ASTRONOMY

NST1010 Astronomy 4 credits The evolution and structure of the universe are explained using underlying basic physical principles along with the historical development of our present understanding. We will explore the instruments and data collection techniques used by astronomers and learn how they can be applied to solve problems in other disciplines. Prerequisites: None

4.00 credits

NST1020 - SUSTAINABLE ENERGY SOLUTIONS

SUSTAINABLE ENERGY SOLUTIONS

NST1020 Sustainable Energy Solutions 4 credits As the world’s current energy demand continues to rise, it is critical to understand the causes, impacts, and possible solutions to our current global energy crisis. This course will focus on the technologies associated with renewable forms of energy and their potential for future success. Prerequisites: None

4.00 credits

NST1030 - ELECTRONICS

ELECTRONICS

NST1030 Electronics 4 credit Foundation Liberal Arts Electronic devices transform the way people work and communicate. This course will focus on understanding the inner workings of those devices to provide a background on what they can and cannot do. We will also explore the impact of resource limitations on electronics, and how electronics can contribute to solving some resource issues. Prerequisites: None

4.00 credits

NST1040 - HUMAN BIOTECHNOLOGY

HUMAN BIOTECHNOLOGY

4.00 credits

NST1200 - CROSS REGISTRATION AT OLIN COLLEGE

CROSS REGISTRATION AT OLIN COLLEGE

4.00 credits

NST1201 - CROSS REGISTRATION AT WELLESLEY COLLEGE

CROSS REGISTRATION AT WELLESLEY COLLEGE

4.00 credits

NST2020 - CASE STUDIES IN ECOLOGICAL MGMT

CASE STUDIES IN ECOLOGICAL MGMT

NST2020 – Case Studies in Ecological Management 4 credit Intermediate Liberal Arts Successful businesses must fully appreciate and understand sustainable management strategies for our vital natural resources. Here we will focus on understanding the ecological principles of natural resource management while exploring new strategies for environmental conservation. Prerequisites: SCNA or NST10%

4.00 credits

NST2030 - CASE STUDIES IN BIOMEDICAL SCIENCE

CASE STUDIES IN BIOMEDICAL SCIENCE

NST2030 Case Studies in Biomedical Science 4 credit intermediate liberal arts An in-depth study of the process for developing and commercializing biomedical technologies. The course explores understanding the role of translational research as a foundation for diagnostic and therapeutic products. The mechanisms underlying selected biomedical devices will also be described. Prerequisites: SCNA or NST10%

4.00 credits

QTM1000 - QM FOR BUSINESS ANALYTICS I

QM FOR BUSINESS ANALYTICS I

QTM1000: Quantitative Methods for Business Analytics I 4 credits THIS COURSE IS FOR STUDENTS WHO STARTED AT BABSON IN FALL 2013 OR LATER. 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

4.00 credits

QTM1010 - QM FOR BUSINESS ANALYTICS II

QM FOR BUSINESS ANALYTICS II

QTM1010: Quantitative Methods for Business Analytics II 4 credits THIS COURSE IS FOR STUDENTS WHO STARTED AT BABSON IN FALL 2013 OR LATER. 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. Prerequisite: QTM1000

4.00 credits

QTM1200 - CROSS REGISTRATION TO WELLESLEY COLLEGE

CROSS REGISTRATION TO WELLESLEY COLLEGE

4.00 credits

QTM2000 - CASE STUDIES IN BUSINESS ANALYTICS

CASE STUDIES IN BUSINESS ANALYTICS

QTM2000: Case Studies in Business Analytics 4 credits – Intermediate Liberal Arts THIS COURSE IS FOR STUDENTS WHO STARTED AT BABSON IN FALL 2013 OR LATER. This course expands on the modeling skills acquired in QTM I and QTM II with special emphasis on case studies in Business Analytics – the science of iterative exploration of data that can be used to gain insights and optimize business processes. Data visualization and statistical techniques, as well as selected optimization methods are used to investigate the relationships between items of interest to improve the understanding of complex managerial models with sometimes large data sets to aid decision-making. These techniques and methods are introduced with Spotfire, a data visualization software, and R, a widely used open-source statistical package, in the context of real-world applications from diverse business areas such as marketing, finance, and operations. Topics covered include advanced methods for data visualization, logistic regression, clustering, modeling with neural nets, and advanced time series analysis. Case studies draw on examples from quality control, database marketing, Prerequisites: QTM1010

4.00 credits

QTM2600 - LINEAR ALGEBRA & DYNAMICAL SYS

LINEAR ALGEBRA & DYNAMICAL SYS

QTM2600 DYNAMICAL SYSTEMS & CHAOS THEORY (Advanced Lib Arts) This course introduces dynamical systems, that is, it investigates how quantities (such as the size of a population, the supply and demand for a certain product, the amount of money in an account, and the amount of a certain drug in the bloodstream) change over time, by analyzing a mathematical relationship between the "present" and the "near future" to make predictions about the "distant future." You will use the mathematical models developed to study problems in finance, cost accounting, economics, population fluctuations, arms race, gambling, fractals, and chaos theory among others. In developing these models we introduce the foundations of Linear Algebra and Markov chains. Prerequisite: QTM1300 or QTM1301 or QTM2300 or QTM1010

4.00 credits

QTM2622 - SPORTS APPLICATION OF MATHEMATICS

SPORTS APPLICATION OF MATHEMATICS

QTM2622 Sports Applications of Mathematics 4 credit advanced liberal arts Mathematicians and statisticians are playing an increasing role in shaping how athletic contests are played and how they are judged. This course examines some of the underlying quantitative principles that are routinely used. Students will apply some statistical techniques (expectations, probability and risk/reward judgments) and some that are deterministic (optimization, ranking and validation.) A variety of software packages will be used to demonstrate the many ways that a mathematical point of view can inform athletes, trainers, administrators and fans. Prerequisites: QTM1010 or QTM2420

4.00 credits

QTM3615 - TIME SERIES AND FORECASTING

TIME SERIES AND FORECASTING

QTM3615 TIME SERIES AND FORECASTING (formerly QTM3671 and QTM3630) 4 credit hours (Advanced Lib Arts) This course will introduce time series models and discuss advanced forecasting methods in the context of real financial data and decision-making situations. The objectives of the course are to provide experience in using time series data (e.g., sales, profits, stock prices, economic indicators, industry sector indicators) to explain the impact of various internal and external factors and predict future trends; to provide a framework for comparing alternative forecasting models for validity, accuracy, and feasibility; to enhance an appreciation for the limitations of forecasting models; to provide exposure and experience in using statistical software to develop forecasting models; and to develop skills at communicating statistical results, and inferences effectively in a managerial context. Teamwork and professional presentation of analysis and recommendations will be required during this course. Prerequisite: QTM2420 or QTM2421 or permission from instructor

4.00 credits

QTM3625 - FINANCIAL SIMULATION

FINANCIAL SIMULATION

QTM3625 (Formerly QTM3673) Financial Modeling Using Simulation and Optimization with Applications to Finance, Marketing, and Management (Advanced Liberal Art) This course is an introduction to quantitative techniques that enable marketing, finance, and management professionals to make optimal decisions under uncertainty. While theoretical background for these techniques is provided, the focus is on their applications and mastering software that is widely used in industry, such as Excel, Solver, @RISK, and MATLAB. Topics include simulation of important probability distributions, bootstrapping, random walks, linear and nonlinear optimization. Lectures draw on examples such as asset allocation under different definitions of risk; index tracking; scenario approaches to project and portfolio management; hedging and arbitrage; and derivative pricing. Prerequisite: QTM2420/QTM2421 or QTM1010

4.00 credits

QTM3674 - CRYPTOLOGY/CODING/THEORY

CRYPTOLOGY/CODING/THEORY

QTM3674 Cryptology/Coding/Theory 4 credits (Advanced Liberal Arts) Cryptology includes the study of both cryptography, the science of developing "secret codes" or ciphers for secure and confidential communication, and cryptanalysis, the breaking of ciphers. Coding theory consists of mathematical techniques for detecting and correcting errors that occur during data transmission. These topics are critical to secure and reliable information exchange, with applications ranging from e-commerce to the transmission of photographs from deep-space to military operations. Through this exploration into the technical, social, and historical aspects of cryptology and coding theory, students will learn and extensively use basic concepts from number theory, finite field and ring theory, matrix algebra, and the software package GAP. Highlighted topics include the RSA cryptosystem, digital signatures, DES, linear and cyclic codes, and the coding theory based McEliece cryptosystem. This course is suitable for students with one year of university-level mathematics, or the equivalent; it should also be interesting for upperclassman from a variety of majors. Prerequisite: QTM1300 OR QTM1000

4.00 credits

QTM3675 - PROBABILITY FOR RISK MANAGEMENT

PROBABILITY FOR RISK MANAGEMENT

QTM3675 Probability for Risk Management The 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: QTM2420

4.00 credits

SCN2420 - BIOTECHNOLOGY

BIOTECHNOLOGY

SCN2420 (formerly SCN2472) BIOTECHNOLOGY (Intermediate Liberal Arts) Biotechnology is a rapidly growing field, encompassing numerous subtopics including stem cell research, cloning, forensics, genetic engineering, and drug discovery. Advances in biotechnology also affect the foods we eat, the medical treatments we receive, and the social environments in which we live. In this course, we will explore the science and ethics of various topics related to the biotechnology and pharmaceutical industries. We will also examine the misconceptions and scientific distortions regarding life science and technology which are prevalent in popular culture. By the conclusion of this course, you will be familiar with the potential of the life sciences industries and how current and future biotech advances affect us as individuals and as humans, as well as other diverse species on Earth. Prerequisite: SCN 13% % - Wildcard

3.00 credits

SCN2430 - ELECTRONIC TECHNOLOGY

ELECTRONIC TECHNOLOGY

SCN2430 (formerly SCN2473) Electronic Technology (Intermediate liberal arts) Study of the application of basic scientific principles and computational skills that allow the understanding of current and potential future thrusts in electronics, computing, microsystems and nanotechnologies. Prerequisite: SCN 13% % - Wildcard

3.00 credits

  1 2