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.

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.

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.

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.

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.

In this course students will learn basic concepts and applications of Artificial Intelligence (AI), including AI project cycles. Instruction will focus on issues surrounding AI including ethics, bias, culture, regulations. Upon completion of this course students will be able to apply AI concepts to organizational solutions.

In this course, students will learn the basic concepts of data analysis and how they are used to drive business processes. Students will learn to identify and retrieve relevant data sources, and to prepare data for analysis with pre-configured and custom tools. Upon completion of this course, students will be able to prepare data for further analysis to drive decision making for business.

All college students, regardless of their college major, need to be able to make reasonable decisions about fiscal, environmental, and health issues that require quantitative reasoning skills. An activity based approach is used to explore numerical relationships, graphs, proportional relationships, algebraic reasoning, and problem solving using linear, exponential and other mathematical models. Students will develop conceptual and procedural tools that support the use of key mathematical concepts in a variety of contexts.