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.
ENERGY AND THE ENVIRONMENT
NST1020 Energy and the Environment
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.
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.
NST1040 Human Biotechnology
4 credit foundation liberal arts
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.
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).
CASE STUDIES IN ECOSYSTEM MGMT
NST2020 – Case Studies in Ecosystems 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.
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.
CASE STUDIES IN SUSTAINABLE FOOD SYSTEMS
NST2040 Case Studies in Sustainable Food Systems
4 credit intermediate liberal arts
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.
CASE STUDIES IN DRUG DEVELOPMENT SYSTEMS
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)
QM FOR BUSINESS ANALYTICS I
QTM1000: Quantitative Methods for Business Analytics I
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.
QM FOR BUSINESS ANALYTICS II
QTM1010: Quantitative Methods for Business Analytics II
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.
CASE STUDIES IN BUSINESS ANALYTICS
QTM2000: Case Studies in Business Analytics
4 credits – Intermediate Liberal Arts
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.
Prerequisite: QTM1010 (or QTM2420)