The Applied Data Science Analytics curriculum allows students to develop theoretical understanding of data analytics and translate theory into practice through hands-on 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:

1. Create effective mathematical solutions to analytical problems.
2. Create effective solutions to computing challenges in analytical projects.
3. Effectively organize and manage datasets for analytical projects.
4. Critically analyze problems and identify analytical solutions.
5. Communicate analytics problems, methods, and findings effectively orally, visually, and in writing.
6. Critically evaluate ethical, privacy and security challenges in data analytics.

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 Resarch and Analytics This course introduces traditional business research methods and business analytics as two sets of tools underlying data-driven business decision making. Students will practice analyzing data, reporting results, interpreting findings, and developing actionable recommendations. Pre-requisites Complete any 1 of the following courses: BUS110 Business Statistics 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. Pre-requisites Complete the following course: BUS171 Information Systems and Operations	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 user-system interfaces. Pre-requisites 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. Pre-requisites 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. Pre-requisites 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. Pre-requisites Complete the following course: DSA250 Fundamentals of Data Science	3
INTDSA303	Internship - Data Science Analytics Internship - Data Science Analytics	3
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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 Statistics This course introduces essential research tools in business. Topics include descriptive statistics of central tendency and variability and hypotheses testing statistical analysis using correlation, analysis of variance, and regression. Problems use applications from business cases, marketing research, and economic policy. Pre-requisites Complete the following course: BUS105 Foundations of Business	3
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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. Pre-requisites 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. Pre-requisites 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. Pre-requisites 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. Pre-requisites 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. Pre-requisites 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). Pre-requisites 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. Pre-requisites Complete the following course: BUS171 Information Systems and Operations	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 hands-on experience through the implementation of database systems, including storage management, query processing, transaction management, and security management. Pre-requisites 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 object-oriented language such as java, python, or C#. Topics covered include user-defined classes, inheritance, polymorphism, data structures such as linked lists, stacks, queues, and trees, sorting and searching algorithms, recursion, event-driven programming and exceptions. Pre-requisites Complete the following course: CMP120 Introduction to Programming	3
DSA200	Data Science Ethics In this course students learn about data science methods from a non-technical 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 pre-requisite for many upper-level math courses and is intended to help students transition from problem-solving 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. Pre-requisites Complete all 2 of the following courses: MTH151 Calculus I MTH152 Calculus II	4
MTH241	Differential Equations Introduction to differential equations. Topics include first-order and linear equations, systems of equations, series solutions, and Laplace transform methods with computer-aided study of numerical solutions, and introduction to partial differential equations, and Fourier series. Three hours of class per week. Pre-requisites 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. Pre-requisites 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. Pre-requisites 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

BUS105	Foundations of Business This course introduces the theory and practice of business and fosters analytical thinking. Students build a foundation for learning by gaining an understanding of business organizations, their structure and functions, the increasingly dynamic and complex global setting in which they compete, and the fundamentals of sustainable business practices.	3
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
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BUS310W	Business Resarch and Analytics This course introduces traditional business research methods and business analytics as two sets of tools underlying data-driven business decision making. Students will practice analyzing data, reporting results, interpreting findings, and developing actionable recommendations. Pre-requisites Complete any 1 of the following courses: BUS110 Business Statistics MTH110 Elementary Statistics PSY213 Statistics and Research Design	3
OR
Prerequisite course for Capstone (xxx490) in the other discipline
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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 user-system interfaces. Pre-requisites Complete the following course: CMP120 Introduction to Programming	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. Pre-requisites Complete the following course: DSA250 Fundamentals of Data Science	3
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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 Statistics This course introduces essential research tools in business. Topics include descriptive statistics of central tendency and variability and hypotheses testing statistical analysis using correlation, analysis of variance, and regression. Problems use applications from business cases, marketing research, and economic policy. Pre-requisites 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. Pre-requisites 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. Pre-requisites 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. Pre-requisites Complete the following course: MTH152 Calculus II	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
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. Pre-requisites Complete all 2 of the following courses: CMP120 Introduction to Programming MTH110 Elementary Statistics	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 user-system interfaces. Pre-requisites 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. Pre-requisites 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. Pre-requisites Complete the following course: DSA250 Fundamentals of Data Science	3
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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 Statistics This course introduces essential research tools in business. Topics include descriptive statistics of central tendency and variability and hypotheses testing statistical analysis using correlation, analysis of variance, and regression. Problems use applications from business cases, marketing research, and economic policy. Pre-requisites Complete the following course: BUS105 Foundations of Business	3
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