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An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

Continuation of CSIT1100 with emphasis on more advanced programming that involve classic data structures such as arrays, dictionaries, linked lists, queues, stacks, and trees. Recursive techniques and efficiency considerations will also be covered. Prerequisite: CSIT1100.

Learn the foundational concepts of artificial intelligence (AI), covering machine learning, deep neural networks, reinforcement learning, natural language processing (NLP), and computer vision. Examine AI applications across various industries, including healthcare, finance, manufacturing, and autonomous systems. Practical expertise is developed through hands-on projects, focusing on building and training AI models to solve real-world challenges effectively. Prerequisite: DSCI1500 Principles of Data Science and Analytics.

A study of the concepts and structures required to implement a database system including the logical design and physical organization of the database. Emphasis is given to the design and development of database systems that includes understanding and applying entity-relationship models. Implementation of a database using SQL on a database system is included.

A study of regression, kernels, support vector machines, clustering, Neural networks. Prerequisites: MATH3340, MATH2510, CSIT1200. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5370 Machine Learning.)

Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

Data analysis and measures of central tendency, dispersion, and correlation. Introduction to probability. Estimation and hypothesis testing. Bivariate regression. ANOVA. Introduction to nonparametric techniques. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.

Limits, continuity, differentiation, and applications including exponential, logarithmic, trigonometric, and inverse functions. Mean value theorem, curve sketching, Riemann sums, and the fundamental theorem of calculus. Prerequisite: 2 years high school algebra. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.

An introduction to the study of accounting dealing with the preparation and analysis of the balance sheet, income statement, and related accounting records. Prerequisites: One MATH course.

The selection and analysis of accounting information for internal use by management. Prerequisite: ACCT2310.

An introduction to the study of auditing principles and standards. Provides a working knowledge of auditing procedures. Prerequisite: ACCT3360.

An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

This course provides students with a comprehensive, end-to-end experience in the execution of a data analytics project. Working collaboratively in teams and using authentic datasets provided by industry or community partners, students engage with clients to define the problem, prepare and analyze data, generate actionable insights, and communicate their findings through professional written reports and oral presentations. With the permission of the instructor, DSCI4700 may also be completed as an Individual Study.

Exposure to accounting methods and taxation policies specific to agricultural producers and businesses. Prerequisite: ACCT2310 Financial Accounting.

Application of economics and financial resource allocation to agricultural businesses from producer to distributor to the end consumer. Content includes equity and credit practices for operations and for capital investments. Prerequisite: ECON1320 Microeconomics.

An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

This course provides students with a comprehensive, end-to-end experience in the execution of a data analytics project. Working collaboratively in teams and using authentic datasets provided by industry or community partners, students engage with clients to define the problem, prepare and analyze data, generate actionable insights, and communicate their findings through professional written reports and oral presentations. With the permission of the instructor, DSCI4700 may also be completed as an Individual Study.

An introduction to economic data and statistical techniques commonly applied in business settings. Topics include understanding the basics of data interpretation, manipulation, and visualization. Students will learn how to carry out and interpret basic linear regression and other methods of statistical analysis in Excel.

Fundamentals of planning, organizing, directing, coordinating, and controlling business activity. Prerequisites: Junior standing.

An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

This course provides students with a comprehensive, end-to-end experience in the execution of a data analytics project. Working collaboratively in teams and using authentic datasets provided by industry or community partners, students engage with clients to define the problem, prepare and analyze data, generate actionable insights, and communicate their findings through professional written reports and oral presentations. With the permission of the instructor, DSCI4700 may also be completed as an Individual Study.

An introduction to economic data and statistical techniques commonly applied in business settings. Topics include understanding the basics of data interpretation, manipulation, and visualization. Students will learn how to carry out and interpret basic linear regression and other methods of statistical analysis in Excel.

A focus on the practice of studying and managing marketing metrics data in order to enhance decision making for marketing efforts including calls-to-action (CTAs), blog posts, channel performance, and thought leadership pieces, and to identify opportunities for improvement and maximize marketing outcomes. Students will learn how marketing analytics professionals serve as liaisons between those who make marketing decisions and those who work with the data.

This course introduces students to the fundamental concepts, tools, and strategies of digital marketing in today's technology-driven business environment. Students will explore core topics such as website optimization, search engine marketing (SEM/SEO), social media, email campaigns, mobile platforms, content creation, and data analytics. Emphasis is placed on developing a strategic mindset-integrating digital channels into cohesive marketing plans, aligning tactics with organizational goals, and leveraging analytics to measure performance and refine decision-making. By the end of the course, students will gain both a theoretical foundation and practical skills to design, implement, and evaluate digital marketing strategies across diverse industries and audiences.

The aim of the course is to give the students a deeper understanding of marketing on a global basis. The students examine the international similarities and differences in marketing functions as related to the cultural, economic, political, social, and physical dimensions of the environment. This course is designed to provide students with an applied understanding of international marketing activities based on real-life examples.

An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

This course provides students with a comprehensive, end-to-end experience in the execution of a data analytics project. Working collaboratively in teams and using authentic datasets provided by industry or community partners, students engage with clients to define the problem, prepare and analyze data, generate actionable insights, and communicate their findings through professional written reports and oral presentations. With the permission of the instructor, DSCI4700 may also be completed as an Individual Study.

Study of theory and practice of modern separation and analytical techniques. Includes use of electrochemical, spectrometric and chromatographic instruments. Additional fee required. Prerequisite: CHEM1420. Offered odd years Spring.

A study of thermodynamics, thermochemistry, chemical kinetics, equilibrium, atomic and molecular structure, electrochemistry, and quantum chemistry. Additional fee required. Prerequisites: CHEM1420, PHYS1420, and MATH1520. Offered odd years Fall. +This course is only offered every other year.

Additional fee required. Continuation of CHEM3610, which is a prerequisite. Offered even years Spring. +This course is only offered every other year.

An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

This course provides students with a comprehensive, end-to-end experience in the execution of a data analytics project. Working collaboratively in teams and using authentic datasets provided by industry or community partners, students engage with clients to define the problem, prepare and analyze data, generate actionable insights, and communicate their findings through professional written reports and oral presentations. With the permission of the instructor, DSCI4700 may also be completed as an Individual Study.

An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

Continuation of CSIT1100 with emphasis on more advanced programming that involve classic data structures such as arrays, dictionaries, linked lists, queues, stacks, and trees. Recursive techniques and efficiency considerations will also be covered. Prerequisite: CSIT1100.

A study of the concepts and structures required to implement a database system including the logical design and physical organization of the database. Emphasis is given to the design and development of database systems that includes understanding and applying entity-relationship models. Implementation of a database using SQL on a database system is included.

A study of regression, kernels, support vector machines, clustering, Neural networks. Prerequisites: MATH3340, MATH2510, CSIT1200. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5370 Machine Learning.)

Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

This course provides a culminating, project-based experience in data science and artificial intelligence. Students work in teams using authentic data sets (often from community or company partners) to define a problem with a client, prepare and analyze data, and develop appropriate analytical and AI/ML solutions. Teams communicate results and recommendations in professional written and oral formats. Prerequisites: CSIT4200 - Machine Learning.

This course provides students with a comprehensive, end-to-end experience in the execution of a data analytics project. Working collaboratively in teams and using authentic datasets provided by industry or community partners, students engage with clients to define the problem, prepare and analyze data, generate actionable insights, and communicate their findings through professional written reports and oral presentations. With the permission of the instructor, DSCI4700 may also be completed as an Individual Study.

An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

This course provides students with a comprehensive, end-to-end experience in the execution of a data analytics project. Working collaboratively in teams and using authentic datasets provided by industry or community partners, students engage with clients to define the problem, prepare and analyze data, generate actionable insights, and communicate their findings through professional written reports and oral presentations. With the permission of the instructor, DSCI4700 may also be completed as an Individual Study.

An introduction to economic data and statistical techniques commonly applied in business settings. Topics include understanding the basics of data interpretation, manipulation, and visualization. Students will learn how to carry out and interpret basic linear regression and other methods of statistical analysis in Excel.

An application of economic theory to the business of sports. Areas include labor economics, public finance, and the theory of the firm. Prerequisite: ECON1320 and either two MATH courses or MATH1360.

Managerial Economics is a course that explores applying economic theories and methodologies to solve business problems and make informed leadership decisions. It focuses on analyzing economic data, understanding market structures, forecasting demand and supply, and evaluating various business strategies in different economic environments.

An exploration of the biotic and abiotic components of the environment, including the biological, physical, and chemical processes that shape natural ecosystems (e.g., biogeochemical cycles). The course will also examine the impact of human population growth, resource use, emissions production, and technological innovations on the environment. Current environmental issues, such as loss of biodiversity, ecosystem degradation, air and water pollution, and climate change, will be considered. Additional fee required. ELO6 Science - Innovation, GE3D Liberal Learning-Natural Sciences

A study of how organisms interact with one another and with their physical environments at the physiological, population, community, and ecosystem levels. Case studies will use ecological concepts to develop conservation strategies for species, habitats, and ecosystems. Prerequisite: BIOL/CHEM1200, BIOL1500, BIOL1520 or instructor's consent. Additional fee required. EL06 Science - World Citizenship, ELO6 Science - Sustainability +This course is only offered every other year.

An exploration of the biotic and abiotic components of the environment, including the biological, physical, and chemical processes that shape natural ecosystems (e.g., biogeochemical cycles). The course will also examine the impact of human population growth, resource use, emissions production, and technological innovations on the environment. Current environmental issues, such as loss of biodiversity, ecosystem degradation, air and water pollution, and climate change, will be considered. Additional fee required. ELO6 Science - Innovation, GE3D Liberal Learning-Natural Sciences.

Study of theory and practice of modern separation and analytical techniques. Includes use of electrochemical, spectrometric and chromatographic instruments. Additional fee required. Prerequisite: CHEM1420. Offered odd years Spring.

An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

Students will learn theoretical and practical foundations related to geographic information systems and spatial analysis. Emphasis on teaching students to integrate and analyze spatial information from various sources. Includes a weekly laboratory section. Prerequisite: MATH1380.

Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

This course provides students with a comprehensive, end-to-end experience in the execution of a data analytics project. Working collaboratively in teams and using authentic datasets provided by industry or community partners, students engage with clients to define the problem, prepare and analyze data, generate actionable insights, and communicate their findings through professional written reports and oral presentations. With the permission of the instructor, DSCI4700 may also be completed as an Individual Study.

Students will learn theoretical and practical foundations related to geographic information systems and spatial analysis. Emphasis on teaching students to integrate and analyze spatial information from various sources. Includes a weekly laboratory section. Prerequisite: MATH1370.

An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

This course provides students with a comprehensive, end-to-end experience in the execution of a data analytics project. Working collaboratively in teams and using authentic datasets provided by industry or community partners, students engage with clients to define the problem, prepare and analyze data, generate actionable insights, and communicate their findings through professional written reports and oral presentations. With the permission of the instructor, DSCI4700 may also be completed as an Individual Study.

A foundational鈥痗ourse鈥痙esigned for students to become informed about health as well as becoming responsible and active participants in the maintenance of their personal health and affecting the health of their community. The鈥痗ourse鈥痠s intended to provide coverage of health promotion, mental health, stress management, afflictions and diseases, aging, environmental health, consumerism and health care and promotion. A grade of C or higher required to count toward the Allied Health major. ELO4 Global Learning - Sustainability.

Presentation of introductory research and writing methods. Introduction to the application of evidence-based practice using various tools to evaluate the research as evidence. This class will result in a final critically appraised topic paper and poster presentation. A grade of C or higher required to count toward the Allied Health major.

A systematic study of the bones, joints, and muscles of the human body as well as internal external forces initiating and modifying movement. Prerequisite: BIOL2300 or BIOL3420 with a grade of "C" or higher. A grade of C or higher required to count toward the Allied Health major.

The principles and practices of energizing the human body for physical exercise. Prerequisite: BIOL2300 or BIOL3440 with a grade of "C" or better. A grade of C or higher required to count toward the Allied Health major.

An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation

Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

This course provides students with a comprehensive, end-to-end experience in the execution of a data analytics project. Working collaboratively in teams and using authentic datasets provided by industry or community partners, students engage with clients to define the problem, prepare and analyze data, generate actionable insights, and communicate their findings through professional written reports and oral presentations. With the permission of the instructor, DSCI4700 may also be completed as an Individual Study.

An introduction to economic data and statistical techniques commonly applied in business settings. Topics include understanding the basics of data interpretation, manipulation, and visualization. Students will learn how to carry out and interpret basic linear regression and other methods of statistical analysis in Excel.

An application of economic theory to the business of sports. Areas include labor economics, public finance, and the theory of the firm. Prerequisite: ECON1320 and either two MATH courses or MATH1360.

An analysis of the field of marketing from a sports perspective with focus on the elements of and development of a marketing plan. Prerequisite: ECON1320.

Introduction to the basic methods of analysis in Data Science and Data Analytics. This course introduces students to the basic statistical methods, coding applications, problem solving, and data integrity issues common to the field.

An introduction to the methods of data science through a combination of computational exploration, visualization, and theory. Students will learn scientific computing basics, topics in numerical linear algebra, mathematical probability, statistics, and social and political issues raised by data science. Prerequisites: Prior courses in statistics, calculus and basic programming. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5300 Introduction to Data Science.)

This course provides a culminating, project-based experience in data science and artificial intelligence. Students work in teams using authentic data sets (often from community or company partners) to define a problem with a client, prepare and analyze data, and develop appropriate analytical and AI/ML solutions. Teams communicate results and recommendations in professional written and oral formats. Prerequisites: CSIT4200 - Machine Learning.

Students will learn skills of data acquisition, methods of data cleaning, imputing data, data storage and other important issues required to producing useable data sets. Codebooks, data standards, and markdown files will be introduced as well as the concept of the data lake. Prerequisites: DSCI4300. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5330 Extracting and Transforming Data.)

This course provides students with a comprehensive, end-to-end experience in the execution of a data analytics project. Working collaboratively in teams and using authentic datasets provided by industry or community partners, students engage with clients to define the problem, prepare and analyze data, generate actionable insights, and communicate their findings through professional written reports and oral presentations. With the permission of the instructor, DSCI4700 may also be completed as an Individual Study.