In this course, students apply data analysis techniques to a real world project. Students will interface with a client data source and prepare the data for analysis to help determine the outcome a industry problem that needs to be solved. Upon completion of this course, students will work in teams to create visualizations, gather business intelligence information, and provide structured data to assist in making a business decision.

In this course, students will learn to use the R programming language to analyze data. Students will learn the syntax and data structures of the R language, and how to apply the language to perform traditional statistical analysis, such as means testing, variable correlations, and linear regressions. Upon completion, students will be able to create R programs to process data and create meaningful output rooted in sound statistical techniques.

In this course students will learn the fundamental concepts in Natural Language Processing (NLP) and text processing. Instructions will focus on knowledge and skills necessary to create language recognition applications. Upon completion of the course students will be able to build an application that processing language to apply to an organizational solution.

In this course, students explore information systems and their role in organizations. They examine management decision support systems, system analysis and design methodologies, information processing technologies, and their role in decision making. Students will explore tools and techniques for supporting and executing organizational processes. Upon completion of the course, students will work as a team to design an information systems solution to meet a specific business need.

Please complete 801-196 Oral/Interpersonal Communication or 801-198 Speech. This is for informational purposes only. Once you register for your course, you can delete this block from your timeline.

In this course students will learn Machine Learning (ML) concepts and Python applications. This will include instruction on data acquisition, supervised and unsupervised learning, and data modeling. Upon completion of this course studnes will able to apply ML concepts to organizational solutions.

This course introduces students to some of the major theories and topics of psychology, including the physiological basis of behavior, personality and learning theories, memory, states of consciousness, stress, research methods, intelligence, human development, psychopathology, and social behavior.

In this course, students will build upon the skills learned in Data Analytics 1. Students will learn to work with large data sets and organize that information for effective data analysis. Students utilize commercial data analysis software packages, and create custom computer programs to analyze data. Upon completion of the course, students will be able to perform analysis of relevant data with various software tools, and use the generated information to help make informed business decisions.

Students taking Introductory Statistics display data with graphs, describe distributions with numbers perform correlation and regression analyses, and design experiments. They use probability and distributions to make predictions, estimate parameters, and test hypotheses. They draw inferences about relationships including ANOVA.

This course is designed for learners to develop knowledge and skills in all aspects of the writing process. Planning, organizing, writing, editing and revising are applied through a variety of activities. Students will analyze audience and purpose, use elements of research, and format documents using standard guidelines. Individuals will develop critical reading skills through analysis of various written documents.