20232024 Course Catalog
Applied Data Science Analytics (BS)
The Applied Data Science Analytics curriculum allows students to develop theoretical understanding of data analytics and translate theory into practice through handson applications. Students can benefit from innovative courses such as Digital Marketing (BUS496), which engages students in the analytics of online advertising and promotion data, and Careers for the Digital Age (IND250), which explores computing and digital skills essential to professionals in the 21st century.
Students can also choose a minor in a specialized field, such as a business field, political science, sustainability, biology, psychology, mathematics, or more.
Learning Outcomes
At the completion of the program, students will be able to:
 The student will be able to utilize research skills in the context of business analytics
 The student will be able to effectively organize and manage data
 The student will be able to formulate analytical solutions to business problems
 The student will be able to communicate analytics problems, methods, and findings effectively
 The student will be able to evaluate ethical, privacy and security challenges in business analytics
 The student will be able to contribute to a team environment to achieve a planned goal
Curriculum

+Major Requirements

BUS171 Information Systems and Operations This course explores basic concepts of communication networks (e.g., the Internet), hardware, software, databases, and systems. Students apply information systems to decision making, communication, collaboration and coordination in the operations of contemporary organizations. Students gain skills in word processing, presentation software, data visualization, spreadsheets, and relational databases.
3 BUS310W Business Analytics II This course builds upon the student’s foundational knowledge of business research and analytics. Students practice a disciplined approach to assessing realworld business problems and applying descriptive, predictive, and prescriptive techniques to solve them. Course activities include discussion forums, case studies, experiential projects, and constructive assessment.
Prerequisites Complete any 1 of the following courses:  BUS110 Business Statistics
 BUS110 Business Analytics I
 MTH110 Elementary Statistics
 PSY213 Statistics and Research Design
3 BUS421 Information and Cybersecurity This course introduces fundamental issues in information and cybersecurity, with an emphasis on vulnerabilities available to cyber attackers. Students develop conceptual tools for identifying vulnerabilities, assessing threats, analyzing risk, and selecting controls to mitigate risk, and practical skills in implementing security, responding to incidents, and designing systems that prevent cyberattacks.
Prerequisites Complete the following course:  CMP283 Database Management Systems
3 CMP120 Introduction to Programming An introduction to the theory and practice of computer programming with an emphasis on problem solving. No previous programming experience is required.
3 CMP283 Database Management Systems This course is a study of database management systems and their applications to a wide range of information processing needs. Students design and implement database management systems while being introduced to a conceptual model of a database environment comprised of five basic components: databases, database management systems, data dictionary/directory systems, database administration, and usersystem interfaces.
Prerequisites Complete the following course:  CMP120 Introduction to Programming
3 DSA250 Fundamentals of Data Science In this course students learn the fundamentals of the data science process, including data acquisition, data cleaning and manipulation to prepare for analysis, common machine learning models for classification and regression, unsupervised machine learning models, and principles of model evaluation.
Prerequisites Complete all 2 of the following courses:  CMP120 Introduction to Programming
 MTH110 Elementary Statistics
3 DSA400W Data Visualization and Communication Cover the different ways of visualizing data, given different types and characteristics of data. Includes assessment and evaluation of existing data visualization techniques. Current tools used transform data and visualize data are reviewed, including Python, Google Charts, and/or Tableau.
Prerequisites Complete the following course:  DSA250 Fundamentals of Data Science
3 DSA411 Machine Learning and AI An introduction to machine learning and artificial intelligence. Topics include classification, regression, clustering, planning, and scheduling. Includes current issues relevant to big data problems.
Prerequisites Complete the following course:  DSA250 Fundamentals of Data Science
3 INTDSA303 Internship  Data Science Analytics Internship  Data Science Analytics
3  MTH110 Elementary Statistics Topics include statistical measures and distributions, decision making under uncertainty, application of probability to statistical inference, linear correlation, introduction to nonparametric statistical methods, and application to problems drawn from the natural and social sciences. Three hours of class per week. Three hours of class per week.
3 OR BUS110 Business Analytics I This course introduces analytical tools that are essential for deriving actionable datadriven solutions to real world business problems. Modules address descriptive statistics, inferential analysis, hypotheses testing, results interpretation, and presentation of key findings. Students utilize diverse sources of data from business cases, research studies, open access datasets, and secondary reports.
Prerequisites Complete the following course:  BUS105 Foundations of Business
3  MTH151 Calculus I This is the first course in the calculus sequence. Topics include differential and integral calculus for algebraic and trigonometric functions with applications. Four hours of class per week.
4 MTH152 Calculus II This is the second course in the calculus sequence. Topics include differential and integral calculus for the transcendental functions, advanced methods of integration, and infinite sequences and series.
Prerequisites Complete the following course:  MTH151 Calculus I
4 MTH221 Linear Algebra Topics include finite dimensional vector spaces, geometry of R, linear functions, systems of linear equations, and theory of matrices and determinants.
Prerequisites Complete the following course:  MTH151 Calculus I
3 MTH222 Multivariate and Vector Calculus An introduction to multivariate calculus using vector spaces, partial differentiation and multiple integration, calculus of vector functions, applications to extremum problems, and differential equations. Three hours of class per week.
Prerequisites Complete the following course:  MTH152 Calculus II
3 MTH244 Discrete Mathematics This course is an introduction to the fundamental logic and mathematical concepts of discrete quantities, as employed in digital computers. Emphasis will be on the careful and precise expression of ideas. Topics include sets and logic, relations and functions, proof techniques, algorithms, combinatorics, discrete probability, graphs, and trees. Three hours of class per week.
3 MTH310 Probability An introduction to the theory of probability and the role of proofs in mathematics. Topics include discrete and continuous probability functions, random variables, expectations, moments, moment generating functions, the central limit theorem, and Chebyshev's inequality. Applications of probability such as queuing theory, Markov processes, and reliability theory also will be covered. Three hours of class per week.
Prerequisites Complete the following course:  MTH152 Calculus II
3 DSA490 Integrative Capstone The integrative capstone is an extended project centered on a major; projects may include laboratory or fieldwork, creative work in the arts, advocacy work, or independent research; projects may be conducted in a group setting. Integrative capstones in the interdisciplinary major must be approved by both academic programs.
Prerequisites Complete all 2 of the following courses:  BUS310W Business Analytics: Research Methods
 DSA250 Fundamentals of Data Science
3 Nine (9) credits of approved electives: choose from list below or get Program Director approval. Only one MTH course permitted. BUS317 Systems Analysis and Design This course introduces information systems analysis and design for contemporary organizations, with a focus on developing critical skills in communicating with people as users, analyzing processes, translating needs into information systems requirements, and testing of prototype ideas. Topics also include functional, structural, and behavioral modeling, and Unified Modeling Language (UML).
Prerequisites Complete the following course:  CMP283 Database Management Systems
3 BUS416 Computer Networking & Telecommunication This course introduces students to the foundational network technologies for data encoding and transmission. Topics may include telephone network and internet architecture, communication protocols (e.g., HTTP, SMTP), transport protocols (e.g., UDP, TCP), and network protocols (IP), TCP/IP, LANs, WANs, circuit vs. packet switching, network security, and multimedia.
Prerequisites Complete the following course:  CMP283 Database Management Systems
3 BUS450 Advanced Database This course examines advanced topics of database management, including system architecture, complex database objects, building database applications, designing data warehouses, and creating database infrastructure to support Big Data analytics. Students gain handson experience through the implementation of database systems, including storage management, query processing, transaction management, and security management.
Prerequisites Complete the following course:  CMP283 Database Management Systems
3 CMP220 Computer Programming II In this course students learn to develop computer programs using a modern objectoriented language such as java, python, or C#. Topics covered include userdefined classes, inheritance, polymorphism, data structures such as linked lists, stacks, queues, and trees, sorting and searching algorithms, recursion, eventdriven programming and exceptions.
Prerequisites Complete the following course:  CMP120 Introduction to Programming
3 DSA200 Data Science Ethics In this course students learn about data science methods from a nontechnical perspective and discuss cases that highlight ethical issues related to data science models, including inherent biases learned from training data, discrimination through proxy variables, lack of transparency, and issues related to privacy and data ownership.
3 MTH215W Introduction to Proof This course introduces students to the process of reading, understanding and writing rigorous mathematical arguments. Additionally, students will become familiar with computer software used for analyzing math problems and typesetting mathematical documents. This course is a prerequisite for many upperlevel math courses and is intended to help students transition from problemsolving oriented classes such as Calculus into courses focused on understanding and writing proofs. Topics include: basic logic, introductory set theory, functions and relations, and quantifiers.
Prerequisites Complete all 2 of the following courses:  MTH151 Calculus I
 MTH152 Calculus II
4 MTH241 Differential Equations Introduction to differential equations. Topics include firstorder and linear equations, systems of equations, series solutions, and Laplace transform methods with computeraided study of numerical solutions, and introduction to partial differential equations, and Fourier series. Three hours of class per week.
Prerequisites Complete the following course:  MTH152 Calculus II
3 MTH256 The History and Theory of Numbers A survey of the history of our number system and theory of numbers. Topics covered include the development of number systems and mathematics from before the sixth century to the present, divisibility, factorization, arithmetic functions, quadratic reciprocity, primitive roots, and diophantine equations. Three hours of class per week.
Prerequisites Complete all 2 of the following courses:  MTH105 College Algebra
 MTH106 Trigonometry
OR Complete the following course: MTH108 Precalculus
OR Complete the following course: MTH151 Calculus I
3 MTH327 Advanced Analysis Foundations for abstract analysis, real and complex number systems, elements of point set topology and limits, continuity, and derivatives.
Prerequisites Complete all 2 of the following courses:  MTH222 Multivariate and Vector Calculus
 MTH215W Introduction to Proof
3 PHI121 Introduction to Logic An introduction to critical thinking, induction, deduction, and contemporary symbolic logic including argument symbolization, proof construction, and truth tables.
3 SUS404 Quantitative Ecology Drawing from case studies in landscape design and natural resource management, this course will apply quantitative methods to ecological data analysis. Students will work with the software program R to apply statistical inference and mathematical modeling using previously collected data sets on single species, species interactions, communities, and food webs.
3 
+Interdisciplinary Major in Applied Data Science Analytics

BUS171 Information Systems and Operations This course explores basic concepts of communication networks (e.g., the Internet), hardware, software, databases, and systems. Students apply information systems to decision making, communication, collaboration and coordination in the operations of contemporary organizations. Students gain skills in word processing, presentation software, data visualization, spreadsheets, and relational databases.
3 BUS310W Business Analytics II This course builds upon the student’s foundational knowledge of business research and analytics. Students practice a disciplined approach to assessing realworld business problems and applying descriptive, predictive, and prescriptive techniques to solve them. Course activities include discussion forums, case studies, experiential projects, and constructive assessment.
Prerequisites Complete any 1 of the following courses:  BUS110 Business Statistics
 BUS110 Business Analytics I
 MTH110 Elementary Statistics
 PSY213 Statistics and Research Design
3 BUS421 Information and Cybersecurity This course introduces fundamental issues in information and cybersecurity, with an emphasis on vulnerabilities available to cyber attackers. Students develop conceptual tools for identifying vulnerabilities, assessing threats, analyzing risk, and selecting controls to mitigate risk, and practical skills in implementing security, responding to incidents, and designing systems that prevent cyberattacks.
Prerequisites Complete the following course:  CMP283 Database Management Systems
3 CMP120 Introduction to Programming An introduction to the theory and practice of computer programming with an emphasis on problem solving. No previous programming experience is required.
3 CMP283 Database Management Systems This course is a study of database management systems and their applications to a wide range of information processing needs. Students design and implement database management systems while being introduced to a conceptual model of a database environment comprised of five basic components: databases, database management systems, data dictionary/directory systems, database administration, and usersystem interfaces.
Prerequisites Complete the following course:  CMP120 Introduction to Programming
3 DSA250 Fundamentals of Data Science In this course students learn the fundamentals of the data science process, including data acquisition, data cleaning and manipulation to prepare for analysis, common machine learning models for classification and regression, unsupervised machine learning models, and principles of model evaluation.
Prerequisites Complete all 2 of the following courses:  CMP120 Introduction to Programming
 MTH110 Elementary Statistics
3 DSA400W Data Visualization and Communication Cover the different ways of visualizing data, given different types and characteristics of data. Includes assessment and evaluation of existing data visualization techniques. Current tools used transform data and visualize data are reviewed, including Python, Google Charts, and/or Tableau.
Prerequisites Complete the following course:  DSA250 Fundamentals of Data Science
3 DSA411 Machine Learning and AI An introduction to machine learning and artificial intelligence. Topics include classification, regression, clustering, planning, and scheduling. Includes current issues relevant to big data problems.
Prerequisites Complete the following course:  DSA250 Fundamentals of Data Science
3  MTH110 Elementary Statistics Topics include statistical measures and distributions, decision making under uncertainty, application of probability to statistical inference, linear correlation, introduction to nonparametric statistical methods, and application to problems drawn from the natural and social sciences. Three hours of class per week. Three hours of class per week.
3 OR BUS110 Business Analytics I This course introduces analytical tools that are essential for deriving actionable datadriven solutions to real world business problems. Modules address descriptive statistics, inferential analysis, hypotheses testing, results interpretation, and presentation of key findings. Students utilize diverse sources of data from business cases, research studies, open access datasets, and secondary reports.
Prerequisites Complete the following course:  BUS105 Foundations of Business
3  MTH151 Calculus I This is the first course in the calculus sequence. Topics include differential and integral calculus for algebraic and trigonometric functions with applications. Four hours of class per week.
4 MTH152 Calculus II This is the second course in the calculus sequence. Topics include differential and integral calculus for the transcendental functions, advanced methods of integration, and infinite sequences and series.
Prerequisites Complete the following course:  MTH151 Calculus I
4 MTH221 Linear Algebra Topics include finite dimensional vector spaces, geometry of R, linear functions, systems of linear equations, and theory of matrices and determinants.
Prerequisites Complete the following course:  MTH151 Calculus I
3 
+Minor Requirements

18 credits
BUS171 Information Systems and Operations This course explores basic concepts of communication networks (e.g., the Internet), hardware, software, databases, and systems. Students apply information systems to decision making, communication, collaboration and coordination in the operations of contemporary organizations. Students gain skills in word processing, presentation software, data visualization, spreadsheets, and relational databases.
3 CMP120 Introduction to Programming An introduction to the theory and practice of computer programming with an emphasis on problem solving. No previous programming experience is required.
3 CMP283 Database Management Systems This course is a study of database management systems and their applications to a wide range of information processing needs. Students design and implement database management systems while being introduced to a conceptual model of a database environment comprised of five basic components: databases, database management systems, data dictionary/directory systems, database administration, and usersystem interfaces.
Prerequisites Complete the following course:  CMP120 Introduction to Programming
3 DSA250 Fundamentals of Data Science In this course students learn the fundamentals of the data science process, including data acquisition, data cleaning and manipulation to prepare for analysis, common machine learning models for classification and regression, unsupervised machine learning models, and principles of model evaluation.
Prerequisites Complete all 2 of the following courses:  CMP120 Introduction to Programming
 MTH110 Elementary Statistics
3 DSA400W Data Visualization and Communication Cover the different ways of visualizing data, given different types and characteristics of data. Includes assessment and evaluation of existing data visualization techniques. Current tools used transform data and visualize data are reviewed, including Python, Google Charts, and/or Tableau.
Prerequisites Complete the following course:  DSA250 Fundamentals of Data Science
3  MTH110 Elementary Statistics Topics include statistical measures and distributions, decision making under uncertainty, application of probability to statistical inference, linear correlation, introduction to nonparametric statistical methods, and application to problems drawn from the natural and social sciences. Three hours of class per week. Three hours of class per week.
3 OR BUS110 Business Analytics I This course introduces analytical tools that are essential for deriving actionable datadriven solutions to real world business problems. Modules address descriptive statistics, inferential analysis, hypotheses testing, results interpretation, and presentation of key findings. Students utilize diverse sources of data from business cases, research studies, open access datasets, and secondary reports.
Prerequisites Complete the following course:  BUS105 Foundations of Business
3 