MAST - Mathematics, Analytics, Science and Technology

AQM1000 Foundations of Business Analytics
4 Foundation Liberal Arts Credits 
 
The course introduces the necessary quantitative methods that are prerequisites to follow-on courses in AQM and in Babson's integrated core business offerings. Statistical software and the use of spreadsheets are integrated throughout so that students better appreciate the importance of using modern technological tools for effective model building and decision-making. The initial third of the course focuses on basic frequentist statistical methods, their conceptual underpinning, such as variability and uncertainty, and their use in the real world. Topics include data visualization, data collection, descriptive statistics, elementary probability rules and distributions, sampling distributions, confidence intervals, and hypothesis testing. The remainder of the course is dedicated to decision-making problems in a managerial context using algebraic, spreadsheet, graphical, and statistical models. Topics include introductions to linear regression, time series analysis, and simulation. The course emphasizes the effective communication of quantitative results through written, visual, and oral means.

AQM2000 Predictive Business Analytics

4 Foundation Liberal Arts Credits

This course is only open to students who started Fall 2021 or after

This course introduces students to the foundational ideas of modern data science through a hands-on implementation in modern statistical software. Students will encounter key conceptual ideas like the importance of holdout data, the dangers of overfitting, and the most common performance indicators for various model types through a tour of popular and practical predictive analytics algorithms: linear regression, k-nearest neighbors, logistic regression, classification and regression trees, naive Bayes’, and others. In addition to these supervised learning models, students will investigate unsupervised learning models like association rules and clustering, which are designed to uncover structure in data rather than predict a particular target. Throughout the course, students will practice communicating the results of their analyses to a variety of stakeholders. 

Prerequisites: AQM1000

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

NST1011: Astrobiology

4 foundation liberal arts credits

Introduction to the new science of astrobiology, study of the origin and evolution of life on Earth, and the search for microbial and intelligent life elsewhere in the Universe. Study of the information necessary to make estimates of the probability of extraterrestrial life, what characteristics it might have and how we might expect to communicate with it if it exists.
 

Prerequisites: None

NST1020 Energy and the Environment
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

NST1030 Electronics
4 Foundation Liberal Arts Credits

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

NST1040 Human Biotechnology
4 Foundation Liberal Arts Credits

This course will provide you with a broad review of the basic scientific concepts, ethical considerations, and practical applications of biotechnology in our daily lives. We will discuss the regulations, technologies, and methods used by academic research laboratories, agricultural and pharmaceutical industries, and forensic scientists. Through this course, you will gain a number of different perspectives on personalized medicine, stem cells, drug discovery, development, and regulation, food, and the environment, all of which are directly connected to human health and well-being. By the end of this course, you will recognize the importance of biotechnology in the world today and see multiple scales of its application from molecular to global levels. You will be able to compare and contrast the positive and negative contributions biotechnology has made to our lives and you will grasp its strengths and limitations as we move forward into the middle of the 21st century.

NST1060 Oceanography
4 Credits

Over 70% of the globe is covered by ocean. Marine systems are a nexus of life – crucial sources of protein for human populations, reservoirs of minerals, and regulators of the global climate. However, human populations have increased demand for ocean resources in greater numbers than is ecologically sustainable. In addition, the ocean serves as a dumping ground for many types of waste, resulting in waters degraded by pollution. The objective of this course is to give you a basic understanding of the physical, biological, and chemical processes driving ocean fundamentals. In addition, we will examine how human demand on marine resources impacts ocean communities.

This course will stress the importance of the scientific method – both in principle and in practice. Extensive discussion of human environmental impacts on the ocean (e.g., climate change, marine pollution, overfishing) will enhance perspectives of self-awareness and ethical decision-making related to social, economic and environmental responsibility and sustainability (SEERS). Critical analysis is emphasized in class discussions, exam questions, lab reports, written assignments, and the group project. Assignments facilitate development of logical communication skills, appropriate use of graphs and tables, and organizing, synthesizing, evaluating and interpreting scientific information. Through lab and group activities, this course fosters team work and ability to work with others. International and multicultural perspectives are integral to the course, since the oceans influence on human populations is global, both directly on the coasts, and indirectly away from the coasts (via weather, climate, and seafood production).

Prerequisites: None

NST1070 Climate and Human Health
4 Credits

This course investigates the interaction between the spheres of natural science and human health. Human activities impact the global climate and the resultant climate change impacts human health, both directly and indirectly. This course focuses on the background of various global health issues and their links to climate using the scientific method and multiple data-driven activities to evaluate research questions. We will also evaluate the integrity of scientific data, assessing reliable sources of information with respect to transparency and scientific bias.

Specific topics covered in this course include the connections between global changes such as sea level and temperature rise with human impacts including increasing climate migration, spread of infectious disease, and threats to food security. We will also investigate connections between industrialized agricultural, fossil fuel use, and the deterioration of water and air quality. Finally, we address the prominent role of environmental racism in the human health and climate connection. In taking this course, students will gain a broader understanding about the long-term effects of their actions, both on themselves as individuals and on other global citizens, and recognize opportunities for individual and systemic changes that result in a more sustainable world.

Prerequisites: None

NST1080 Paradigms of Scientific Invest
4 Foundations Liberal Arts Credits

A multidisciplinary examination of the principles of scientific research and routes to discovery with examples from the history of the subject from its Greek beginnings to modern times. The course will provide insight into the sources, motivations, and methods of approach utilized by the developers of modern science. Topics from biology, physics, and engineering will be used to discover how we unravel the mysteries of the natural world and address the question of how do we know what we know is true by critically examining how the science community has resolved conflicting interpretations of the natural world and analyzing the consequent paradigm shifts from previously accepted theories. These concepts will be applied to addressing societal challenges in developing a national science policy, why things go wrong and mitigating man-made disasters. Finally, the real-world utility of these concepts is applied to applications within an entrepreneurship context in terms of evaluating and managing technology ventures.

Prerequisites: None

NST1090 Science of Sport

4 NST1 Credits

From the first recorded event at the ancient Olympic Games in 760 BC to the present, humans have long been captivated by sports. Humans are competitive by nature, and while sports are thrilling to both watch and play, sports are also a powerful demonstration of science. Every sport from soccer to cricket, baseball to softball, football, swimming and track and field all involve a complex symphony of science, technology, engineering, and math. This course will explore the science that underlies sport, specifically incorporating the traditional scientific disciplines of anatomy and physiology, physics, psychology, biomechanics and math. We will explore the systems of the human body that make it possible for a pitcher to throw a baseball at 100 mph, a marathoner to run 26.2 miles in just under 2 hours or a figure skater to land a quadruple axle. We will explore how science contributes to the limits of human speed, strength and endurance. We have accumulated considerable amount of information that contributes to our understanding of health, the human body and human performance in relation to sport and exercise. We will explore a range of topics from the effects of exercise on heart rate, oxygen consumption, muscle function and fatigue, joint mechanics, metabolism and concussion. Importantly, we will put the concepts we learn in class into practice in the lab and on the field to test them and collect and use data to critically analyze athletic performance and the underlying scientific principles that define it.

Prerequires: None

NST2011 Socio-Ecological Systems and Disaster Resilience  
4 Advanced Liberal Arts Credits

**NST2011/ECN2611: Socioecological Systems and Disaster Resilience will be co-taught by Prof. Winrich and Prof. Way as a single course.** **These are two separate courses and students are held responsible to register for the course that they would like to receive credit for.** 

Natural disasters can affect us wherever we go. Disasters might be localized or far-reaching, and may come from severe weather, seismic events, biological catastrophe, or outer space. Natural disasters may seem random, but their impact on people and their communities is not. While natural systems spark an event, like an earthquake, the “disaster” is often the result of economic, political and social systems. And in the case of climate change, the economic system itself may be the catalyst for ever-more-destructive natural forces such as hurricanes, floods and wildfires, potentially creating a negative feedback loop that leads toward more destructive events, both natural and man-made. This course looks at the rising number of natural disasters in the context of the economic systems that impact the environment and put communities in harms’ way. It investigates the connections between humans and the environment when they are impacted by anticipated and unanticipated natural events, and how they plan for the future. It explores resilience planning for more survivable, sustainable communities in the face of disasters. It specifically looks at the role of economic systems and how these systems can either worsen or mitigate the severity of natural disasters themselves. 

Prerequisites: AHS1000 and RHT1000 and RHT1001 and NST1

NST2020 Case Studies in Ecosystems Management
4 Intermediate Liberal Arts Credits

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: NST10%

This course is not equivalent to HSS2080. Please disregard the note indicating equivalency. The system is not able to correct this at this time.

NST2040 Case Studies in Sustainable Food Systems
4 Intermediate Liberal Arts Credits

What is food – where does it come from, how is it grown, what resources does it use, what’s the difference between a GMO and an organic product, what do labels mean, is it sustainable? This course looks to take a scientific and systems based look at the food we eat and deeply examine all of the steps that occur between “farm to table”. We need food to survive and food must be grown, cultivated, harvested, processed, and distributed so that we can benefit from it. These steps take place in different ways all across the globe, across the country, and among our neighbors. In this class, we’ll look at what it means to be a sustainable food system, look at historical approaches that worked to meet/deviate from this goal, and look at how the future aims to feed a growing world with increasingly diminishing resources.

By the end of this course, you will recognize the importance of sustainable food systems and know the different areas that comprise this system. You will be able to distinguish between sustainable and non-sustainable food systems. Through this design, this course meets the college learning goals of Rhetoric, Quantitative and Information Analysis, Ethics and SEERS, and Critical and Integrative Thinking.

Prerequisites: NST10%%

NST2060 Case Studies in Drug Development Systems
4 Intermediate Liberal Arts Credits

Drug development is a dynamic, multidisciplinary industry that encompasses the discovery, scientific, clinical and economic assessment of a new compound’s safety, efficacy, potential side effects and requires the collaboration and innovation of scientists, chemists, clinicians, statisticians, lawmakers, business leaders and entrepreneurs. Over the last 30 years, the idealized goal of drug discovery has been to identify a specific chemical substance that is highly specific for a single molecular target and arrests or stems the advancement of disease. Although the goal is highly specific and the process seems linear, there are many contributing, and often unforeseen factors that inform drug design, the drug development pipeline and the eventual success or failure of a given drug candidate. In this course, we will take a systems approach to identify and describe all of the contributing elements of identifying, characterizing and bringing a drug to market, to define the physiological, biological, economic and regulatory systems that characterize the process and to outline the social, economic and environmental considerations of a sustainable and productive model for drug development.

Prerequisites: NST10XX (NST 1)

NST2070 Astrobiology and the Emergence of Complex Systems
4 Intermediate Liberal Arts Credits

The prospects for simple and intelligent life beyond earth are discussed in terms of planetary science, molecular biology, complexity theory, evolution and thermodynamics. Discussions will focus on the processes leading to the emergence of complex systems as well as the biological and physical interdependencies of life and the environment.

Prerequisites: NST10XX

NST2085 Socio-Ecological Prairie Systems
4 Intermediate Liberal Arts Credits

**NST2085 AND LVA2085 are two separate courses and students are held responsible to register for the course that they would like to receive credit for.**

Socio-ecological systems (SES) are linked systems of people with nature, emphasizing that humans must be seen as a part of, not apart from nature.  This course will explore the nature of the prairie, both as a socio-ecological system and as a subject for exploration and contemplation for visual and literary artists.  Before the Euro-American (un)settlement of the North American middle west—about 150 years ago—the tallgrass prairie extended for approximately 145 million acres from Canada to Texas.  Now, after several generations of overgrazing, plowing, and the intensities of agricultural production, there remains less than 5% of what some scientists call our most endangered ecosystem.  We will investigate how prairies function, study the causes and consequences of related ecological patterns and processes in prairie landscapes, describe both the loss and restoration of prairie environments, and appreciate the potential for the role of the arts in naming, analyzing, and imagining solutions relating to the examination and repair of prairie systems.  Studying SES allows for the development of important skills for future leaders, such as approaches for incorporating uncertainty, nonlinearity, and self-reorganization from instability. Transdisciplinary approaches will be employed to address complex temporal, spatial, and organizational scales to investigate real world challenges.

Prerequisites: NST1 and FCI1000 and WRT1001

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

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

QTM2000 Case Studies in Business Analytics
4 Intermediate Liberal Arts Credits

This course builds on the modeling skills acquired in the QTM core 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 predictive analytics techniques 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 widely used commercial statistical packages for data mining and predictive analytics, in the context of real-world applications from diverse business areas such as marketing, finance, and operations. Students will gain exposure to a variety of software packages, including R, the most popular open-source package used by analytics practitioners around the world. Topics covered include advanced methods for data visualization, logistic regression, decision tree learning methods, clustering, and association rules. Case studies draw on examples ranging from database marketing to financial forecasting. This course satisfies one of the core requirements towards the new Business Analytics concentration. It may also be used as an advanced liberal arts elective or an elective in the Quantitative Methods or Statistical Modeling concentrations.

Prerequisites: QTM1010 (or QTM2420)

QTM2600 Linear Algebra

4 Advanced Liberal Arts Credits

Linear Algebra provides the mathematical background for modern applications in statistics and data science.  In this course we study linear algebra beginning with the classic but still essential application of solving systems of linear equations.  We use this as an entry to think of the properties of high dimensional spaces, and the relationships between those spaces.  Students will learn how to compute with matrices and see their application to diverse areas such as cryptography, image recognition, page rank in computer searches and establishing fair ranking and voting systems.

Prerequisites: AQM2000

QTM2601 Applications of Discrete Math 
4 Advanced Liberal Arts Credits 

Discrete Mathematics is used whenever objects are counted, when relationships between finite sets are studied, and when processes involving a finite number of steps are analyzed. The kind of problems solved may include: How many ways are there to choose a valid password on a computer network? What is the shortest path between two cities using a transportation system? How can a circuit be designed that adds integers? You will learn about the discrete structures and techniques found in Mathematical Logic, Combinatorics, Graph Theory, and Boolean Algebra that are needed to understand and solve these and other problems. You will develop mathematical maturity and problem-solving skills by studying models in such diverse areas as Computer Science, Communications Networks, Business, Engineering, Chemistry, and Biology. 
 

Prerequisites: AQM1000 This course is typically offered every 3rd semester

QTM2622 Sports Applications of Mathematics
4 Advanced Liberal Arts Credits

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: AQM2000

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 QTM2000.

Prerequisites: QTM2000 or permission from the instructor

QTM 3600: Data Science Field Project

4 Advanced Liberal arts credits

The course will provide students with the opportunity to reinforce their skills in data science, including but not limited to data acquisition, data preparation/wrangling, exploratory data analysis/visualization, model building, testing, presentation, and deployment by coaching them through a real-world, data-intensive project. The course will consist of two main components:

• A structured curriculum designed to enhance students’ data science and analytics skills for implementing analytical projects and effectively communicating their results to management and other stakeholders;

• A consulting project in which student teams will be tasked with solving a real-world problem presented by an external organization or partner, utilizing techniques and methodologies from data science and analytics. Under the supervision of the instructor, student teams will work on the assigned problem throughout the semester, communicating with the external organization/partner during the project and presenting their results periodically throughout the project. Despite being a group project, the workload will demand each student to dedicate significantly more time to the course compared to AQM courses that do not involve work with an external organization/partner.

This course satisfies the Advanced Experiential learning requirement through an extensive project involving an external organization/partner.

Prerequisites: AQM 2000 (QTM 2000 in the older curriculum)

QTM 3601: Deep Learning in Business

4 advanced liberal arts credits

This course is dedicated to learning a type of artificial intelligence through building neural network models that mimic the human brain to solve complex business problems, which involves a variety of data types like text, image, sequential, etc. The course will build on analytical concepts learned from the AQM2000 (Predictive Business Analytics) course and introduce other unsupervised and self-supervised machine learning concepts in types of neural networks, natural language processes, and reinforcement learning. Each concept contains topics like model building and parameter tuning through optimization, regularization, etc. These advanced topics will be discussed in the context of practical real-world applications such as prediction, classification, image recognition, text analysis, gaming, etc. The implementation of the introduced topics will be carried out in Python programming language.

Prerequisites: AQM 2000

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: AQM2000

QTM3610 Applied Multivariate Statistics

(Formerly QTM2610)
4 Advanced Liberal Arts Credits

This course extends the modeling tools presented in prior statistics courses and focuses on the application and validation of models developed using real data in the context of finance, economics, and marketing research. Examples of applications include modeling the impact of advertising on sales, admission yields for business schools, patterns of voting behavior and a variety of survey data. This course focuses on implementing data analysis techniques using a statistical software package and interpreting the results in a decision-making environment. Emphasis is placed on understanding the limitations of modeling approaches, as well as the diversity of potential applications in business.

Prerequisites: AQM2000

QTM3615 Time Series and Forecasting
4 Advanced Liberal Arts Credits

This course is about the analysis of time series data in the context of various real-life forecasting situations pertaining to business and non-business areas, such as sales, banking, healthcare, sports, and global warming. The objectives of the course are: to provide practical experience with time series data to predict future outcomes; to provide a framework for comparing alternative models in terms of predictive accuracy; to cultivate an appreciation of various types of times series modeling approaches; to provide advanced exposure and experience in programming to build, test, and apply time series models; and to develop skills at communicating results effectively. The software used throughout the course will be Excel and R/RStudio. Effective teamwork and professional presentation of analyses and recommendations will be required during this course.

Prerequisites: AQM2000 or permission from instructor

QTM3620 Optimization Methods and Applications
(Formerly Operations Research)
4 Advanced Liberal Arts Credits

This course provides an introduction to optimization techniques for decision making with spreadsheet implementation. Topics covered include linear programming, sensitivity analysis, networks, integer programming, nonlinear programming, and multiple objective optimization. Models discussed span different business disciplines including finance, accounting, marketing, human resources, economics, operations, and project management. Throughout the course, learning is reinforced via hands-on computer experience using problems and cases.

Prerequisites: AQM2000

QTM3625 Financial Modeling Using Simulation and Optimization with Applications to Finance, Marketing, and Management
4 Advanced Liberal Arts Credits

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.

Prerequisites: AQM2000

QTM3630 Time Series Analysis 
(Formerly QTM3671 Forecasting Methods) 

Advanced Liberal 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. 

Prerequisites: QTM2420 or QTM2421 or permission from instructor

QTM3635 Quantitative Methods for Machine Learning
4 Advanced Liberal Arts Credits

The 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: AQM2000

QTM3674 Cryptology/Coding/Theory
4 Advanced Liberal Arts Credits

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.

Prerequisites: AQM1000

QTM3675 Probability for Risk Management

4 Credits

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: AQM2000

SCN3600: Biomimicry Applying Natures Design for Business

4 advanced liberal arts credits

In this course we will investigate the tools and principles of biomimicry, which seek to sustainably solve current challenges by taking inspiration from how nature solves these same problems. Nature provides us with an incredible amount of research and development for effective problem-solving methodologies with the ultimate test for organisms being survival of the fittest. For the past 3.8 billion years, life has evolved strategies that are constantly integrated and optimized to create conditions conducive for life to continue. Successful examples of biomimicry include something as simple as Velcro (imitating burrs that stick to sheep) to cutting edge advancements like a bionic leaf producing hydrogen fuel from sunlight (imitating photosynthesis) and medical grade internal adhesives (imitating how mussels adhere underwater).

In this course we will begin by exploring design principles in biology, chemistry and physics and applying them to specific technological design strategies by asking questions like “How does nature make color?” and “How does nature water-proof something?” Then we will explore ecological design principles to understand how we can use nature’s strategies of interconnectedness and cycling as a way to solve problems in businesses and organizations and move toward the circular economy. This course will emphasize the development of skills in critical thinking, synthesis of information, scientific literacy, hand-on exercises, and current topical issues in biomimicry.

Prerequisites: NST1XXX

SCN3601: Triumphs and Trials of the Pharmaceutical Industry

4 advanced liberal arts credits

In 2022, the US pharmaceutical market was valued at over $1.2 trillion, forecasted to reach more than $2 trillion dollars by the year 2025. Bringing a new drug or therapeutic agent to the market is a complex process that can take upwards of a decade with a hefty price tag upwards of $2 billion dollars. The United States pharma industry spends about $60 billion yearly on drug research and development, generating approximately half of the $1.2 trillion market. As a result of this significant investment, the pharma industry has made great strides in the treatment of many diseases and developed therapies that have changed the world, including the development of antibiotics to treat infection and drugs like insulin, which have saved hundreds of thousands of lives Research, technological advances and development have led to new and innovative approaches to treat cancer, has reduced HIV infection from a 100% mortality rate to a chronic illness in the US and led to the development of a vaccine against COVID19 in record time. Despite making many significant scientific strides, public opinion of the industry is lower than ever before. It has been plagued with controversy after controversy about questionable practices including intellectual property arguments, skyrocketing costs, exorbitant executive payouts and inequitable vaccine access across the world. Additionally, a seemingly arbitrary drug pricing system and the indisputable role the pharma industry played in the opioid crisis, have fed into the significant public relations problem the industry currently faces. This course will focus on real world considerations that drive both the good and the bad of the pharmaceutical industry. We will discuss the triumphs and challenges that occur in bringing a drug from bench to bedside, and explore some of the questionable practices that have been connected to the industry. We will discuss the process and impacts of new drug development, translational medicine, and drug pricing models, investigating the ethics of balancing patient access, scientific innovation and the sustainability of a complex and often inefficient system. By the end of this course, students will appreciate the complexity of drug development system and understand the critical scientific and ethical challenges the pharmaceutical industry faces in bringing a drug to market.

Prerequisites: Any NST1XXX course

SCN3602: Eclipses on Earth

4 Advanced Liberal Arts Credits

This course will involve an in-depth exploration of the Sun-Earth-Moon system and how that system results in eclipses. From understanding how the relationship between the Sun, Earth, and Moon generate eclipses, we will discuss the different types of eclipses, and explore the prediction of eclipses. We will consider the historical explanations and uses of eclipses in both the social and scientific realms. We will also examine the history of solar observations to understand safe solar viewing practices. This course is designed to fulfill the advanced experiential component of the curriculum as well. In teams you will work with local teachers and libraries to develop ways of teaching about eclipses to K-12 students and a general audience. You will also assist in developing safe solar viewing plans for your external “clients” on the eclipse day.

Prerequisites: NST 10XX

SCN 3603: Biotechnology and Innovation

4 advanced liberal arts credits

In Biotechnology and Innovation, students will explore the dynamic intersection of biotechnology and business, focusing on the impact that scientific research has had on the development of new products, services, and startups within the biotech industry. The global biotechnology market, currently valued at approximately $735 billion is predicted to reach over $1.1 trillion by 2026.  This course will cover the fundamental scientific aspects of biotechnology and biotechnology entrepreneurship with a focus on the global problems that can be solved using biotechnology innovations.   It will explore the pioneering scientific innovations using living cells and their molecules that drive the industry, including breakthroughs in genetic engineering, gene editing, regenerative and personalized medicine, synthetic biology and bioinformatics. Students will analyze how these scientific advancements translate into commercial opportunities.  Case studies of successful biotech products and services that have reshaped healthcare, agriculture, food systems, environmental challenges, bioremediation, biofuel production and many other industrial applications will also be explored. This will allow students to gain insight into the processes by which scientific discoveries become marketable solutions. This course will leverage the fact that Massachusetts is the #1 hub of Biotechnology in the world, giving students the opportunity to work with an industry partner to help solve a real-world problem. Students will participate in a semester-long project where they meet with industry stakeholders to analyze a problem and propose actionable solutions.  By the end of this course, students will have a thorough understanding of the basic foundational knowledge central to biotechnology, and a better understand how scientific research serves as the foundation of the development and commercialization of biotechnological innovations.

Prerequisites: NST 10%%

SCN 3604: Green and Blue Technology Solutions

4 advanced liberal arts credits

Green and blue technologies, (also collectively referred to as “cleantech”, “greentech”, or “envirotech”), use science to understand and address negative impacts and promote new approaches to support human activity and economic growth that are less harmful to natural systems. While emergent green and blue technologies often hold promise of creating a more sustainable future, there is a wide range of associated challenges to seeing them adopted and in some cases avoiding unintended consequences of such adoption. 

In this course we will explore different technology solutions across three thematic areas:  Climate Change Mitigation and Adaptation, Resource Use, and Pollution Control. We consider the role that technology can play in addressing socio-ecological challenges and develop a framework for evaluating emerging technologies and designing new ones. The course will also include opportunities for students to engage with professionals in cleantech fields. The course will host a guest speaker for each of the three themes of the course (climate, resources, pollution). The course will also offer optional field trips that will allow students to observe and experience different local initiatives to develop cost effective sustainable technologies. The overall goal of this course is for students to develop the tools and thinking necessary to understand our current, critical environmental challenges and identify the role that technology and business may play in developing solutions that are efficient, equitable, and sustainable.

Prerequisites: NST 10%%

SCN3615 Ecology of Animal Behavior
4 Advanced Lib Arts Credits

The study of the nature, variety and function of the fundamental types of animal behaviors. Communication, habitat selection, predation and antipredator defense, reproductive strategies, tactics and mating systems, and play and social behaviors will be compared and analyzed, and applications to human behavior will be discussed.

Prerequisites: NST10%
% - Wildcard

SCN3630 Economics Botany
Advanced Liberal Arts

This course will investigate the relationship between plants and society. Without plants and plant products humans would be hungry, naked, and lacking oxygen to breath. We will begin by exploring the basics of different plant parts and how plants grow and reproduce. We will then examine plants as sources of food, materials, perfumes, drugs, and medicines. Throughout the course we will discuss the role plants have played in influencing economics, language, politics, and religion. Current topics of particular interest for this course include the debate over genetically engineered crops, the development of new pharmaceutical medicines, the changes in human diet, and the use of plant products in new technologies. This course will emphasize the development of skills in critical thinking, synthesis of information, science literacy, hand-on exercises, and current topical issues in plant biology.

Prerequisites: NST I

SCN3635 Human Nutrition
(Formerly Personal Nutrition)
4 Advanced Liberal Arts Credits


Every day we are bombarded with information about diet and health, often confusing and contradictory. As consumers, it is difficult to separate fact from fad, truth from fiction. This course will provide a foundation in basic nutrition, including anatomy and physiology of the digestive tract and the development of disease, with the goal of applying this information to aid in making informed choices in the treatment and prevention of nutrition related disease. We will also explore how the personal actions a student can take to encourage a sustainable diet, defined as “food choices that maximize personal health while minimizing the impact on the environment.

Prerequisites: NST10%

SCN3640 Science and Innovation
4 Advanced Liberal Arts Credits

An examination of the concepts, principles and policies related to research and development activities with examples from the history of the subject from its Greek beginnings to modern times. Successful and failed R&D projects from multiple disciplines will be explored as a driving force for innovation. The complex relationships that the scientific and engineering enterprises have to the innovation process will be examined with respect society, industry, and political motivations.

Prerequisites: NST10%%
 

SCN3660 Human Health and Disease
4 Liberal Arts Credits

This class explores human health and disease. We identify the biological roots of infection, exploring advances in medicine and related disciplines. We analyze all facets of risk - from genetics to lifestyle - proceeding topically through major threats to human longevity and quality of life. Topics include the latest understanding of chronic illness - cancer, stroke, heart disease - that account for most premature mortality in the developed world. We will examine strategies to protect our health and to ameliorate some of the consequences of aging; we will investigate new challenges, such as emerging infections and eating disorders. Psychological aspects of wellness are discussed as well.

Prerequisites: Foundation Science

SCN3665 Global Climate Change 
4 Advanced Liberal Arts Credits 

Global climate change is one of the most contentious, yet critically important issues facing the world today. However, the science behind climate patterns and the influence of human actions on global climate are not always well understood. This course is designed to investigate scientific knowledge and uncertainty regarding past, present and future changes in the earth’s climate, and how scientists study and predict patterns of climate change. We will investigate the known relationships between the earth’s atmosphere and global climate, historic patterns of climate change, recent observations of changes in global climatic conditions, how scientists develop models and conduct experiments to predict future change, and the myriad of predicted ecological, economic and societal shifts that may occur. Finally, we will discuss options to mitigate climate change impacts, public perception and media portrayals of climate change, and ethical considerations related to climate change. 

Prerequisites: Foundation Science

SCN3689 Crime Science
4 Advanced Liberal Arts Credits

This course examines the role that the modern natural sciences play in analyzing physical evidence collected at a crime scene. It begins by defining forensic science and understanding why the government has placed special qualifiers on scientific expert witnesses and their testimony. Students will survey the sciences used in a modern crime lab to understand the principles behind the analyses. Historical and current crimes and their trials as well as a mock crime scene will highlight lecture material. Disciplines that will be covered include Toxicology, Controlled Substances, Arson, DNA, Blood Splatter, Friction Ridge, Ballistics, and Crime Scene Processing.

Prerequisites: NST1

SES2000 Socio-Ecological Systems

4 Credits

Special Topic Descriptions: https://babson.sharepoint.com/:w:/s/SESTeachingFaculty/EWYrFfzN_uZDhS_m8w-TmAcBP35aZg1XkbeRQAjsQ7HapQ?e=pc4LSt&CID=4F7F0C1A-ED6A-4E61-9AB9-A0476C8E2B98 

This co-taught course will integrate across the social sciences and ecological sciences to focus on socio-ecological  systems(SES), which are linked systems of people with nature, emphasizing that humans must be seen as a part of, not apart from nature. These connected systems are complex, adaptive, and are governed by feedbacks within and  between social and bio-physical processes. Studying SES allows for the development of important skills desperately  needed for future business leaders, such as approaches for incorporating uncertainty, nonlinearity, and self-reorganization from instability. Students will be taught systems thinking and how to identify and develop an  understanding of the interdependent and interrelated structures and feedbacks of dynamic systems.  Transdisciplinary approaches will be employed to address complex temporal, spatial, and organizational scales to  investigate real world challenges. Beyond just social impact businesses or corporate social responsibility, teaching  system dynamics for sustainability allows students to develop as system change leaders.  

This course will directly address the new integrated sustainability theme and will provide a strong background for all  of our students in integrative systems thinking, ecological integrity, and structural injustice. Students will be  introduced to the UN Sustainable Development Goals, Planetary Boundaries Framework, resilience strategies, and leverage points for systems-based change for sustainability. Students will also learn concept mapping techniques as  a way of visually representing complex systems, their relationships, and indirect connections and feedback effects.  The skills learned can then be expanded and built from in subsequent elective courses. There are multiple content versions of this course including Climate Systems, Food Systems, Natural Disaster and Resilience Systems, Prairie Systems, Urban Systems, and Water Systems that are offered across different semesters.

Prerequisites: NST 10XX and FCI 1000 and WRT 1001