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Math and Science Division Course Listings

Undergraduate

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QTM2601 - APPLICATIONS OF DISCRETE MATH

APPLICATIONS OF DISCRETE MATH

QTM2601 APPLICATIONS OF DISCRETE MATH (Advanced Lib Arts) 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. Prerequisite: QTM1000 or equivalent (such as QTM1300, QTM1301, or QTM2300 from the old curriculum). This course is typically offered every 3rd semester.

4.00 credits

QTM3610 - APPLIED MULTIVARIATE STATISTICS

APPLIED MULTIVARIATE STATISTICS

QTM3610 (formerly QTM2610) Applied Multivariate Statistics (Advanced Lib Arts) 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 Prerequisite: QTM2420 or QTM2421 or QTM1010 This course is typically offered in the following semester: Spring

4.00 credits

QTM2420 - APPLIED QUANT MODELING

APPLIED QUANT MODELING

QTM2420 Applied Quantitative Modeling (Intermediate Lib Arts) THIS COURSE IS FOR STUDENTS WHO STARTED AT BABSON BEFORE SEPT. 2013 This course explores ill-defined problems 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, linear optimization, and use of spreadsheets is essential because these concepts are extended and reinforced throughout the course. Topics include applied multiple linear regression, basic time series analysis (including decomposition techniques), linear programming, basic decision analysis, and simulation. The course emphasizes the use of appropriate software and the latest technological methods for accessing data. This course is typically offered in fall and spring semester and summer session. Prerequisite: QTM1310 or QTM1311

3.00 credits

QTM2420 - APPLIED QUANT MODELING

APPLIED QUANT MODELING

QTM2420 Applied Quantitative Modeling (Intermediate Lib Arts) THIS COURSE IS FOR STUDENTS WHO STARTED AT BABSON BEFORE SEPT. 2013 This course explores ill-defined problems 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, linear optimization, and use of spreadsheets is essential because these concepts are extended and reinforced throughout the course. Topics include applied multiple linear regression, basic time series analysis (including decomposition techniques), linear programming, basic decision analysis, and simulation. The course emphasizes the use of appropriate software and the latest technological methods for accessing data. This course is typically offered in fall and spring semester and summer session. Prerequisite: QTM1310 or QTM1311

3.00 credits

QTM2420 - APPLIED QUANT MODELING

APPLIED QUANT MODELING

QTM2420 Applied Quantitative Modeling (Intermediate Lib Arts) THIS COURSE IS FOR STUDENTS WHO STARTED AT BABSON BEFORE SEPT. 2013 This course explores ill-defined problems 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, linear optimization, and use of spreadsheets is essential because these concepts are extended and reinforced throughout the course. Topics include applied multiple linear regression, basic time series analysis (including decomposition techniques), linear programming, basic decision analysis, and simulation. The course emphasizes the use of appropriate software and the latest technological methods for accessing data. This course is typically offered in fall and spring semester and summer session. Prerequisite: QTM1310 or QTM1311

3.00 credits

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

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

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

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

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

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

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

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

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

QTM2000 - CASE STUDIES IN BUSINESS ANALYTICS

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. Prerequisite: QTM 1010 or QTM 2420. For Business Analytics concentrators who started at Babson before Fall 2013, QTM 2000 is equivalent to QTM 3650, which is no longer offered.

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 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. Prerequisite: QTM 1010 or QTM 2420. For Business Analytics concentrators who started at Babson before Fall 2013, QTM 2000 is equivalent to QTM 3650, which is no longer offered.

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 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. Prerequisite: QTM 1010 or QTM 2420. For Business Analytics concentrators who started at Babson before Fall 2013, QTM 2000 is equivalent to QTM 3650, which is no longer offered.

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 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. Prerequisite: QTM 1010 or QTM 2420. For Business Analytics concentrators who started at Babson before Fall 2013, QTM 2000 is equivalent to QTM 3650, which is no longer offered.

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 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. Prerequisite: QTM 1010 or QTM 2420. For Business Analytics concentrators who started at Babson before Fall 2013, QTM 2000 is equivalent to QTM 3650, which is no longer offered.

4.00 credits

QTM2000 - CASE STUDIES IN BUSINESS ANALYTICS

CASE STUDIES IN BUSINESS ANALYTICS

QTM 2000 – Case Studies in Business Analytics 4 Credits – Intermediate Liberal Arts Note: For students who started at Babson before Fall 2013, this course can count as an elective, QTM 3650. For students who started at Babson Fall 2013 or later, this course can count as a third Quantitative Methods course. The course is required for the Business Analytics concentration. 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. Prerequisite: QTM 1010 or QTM 2420

4.00 credits

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