Examines proven strategies designed to help learners achieve greater personal, academic, and professional success. Learners will apply personal responsibility thinking and behaviors; self- management, awareness, and motivation strategies; as well as interdependence skills to develop a proactive life plan.

Introduces the field of IT software development and design. Learners will explore degree and career paths, IT tools and processes and begin to demonstrate professional communication. Learners will create or modify a simple computer program using an integrated development environment.

Discover the various technical and administrative aspects of information security and assurance. This course provides the foundation for understanding the key issues associated with protecting information assets, determining the levels of protection and response to security incidents and designing a consistent, reasonable information security system, with appropriate intrusion detection and reporting features.

Introduces computer programming and terminology in the Python programming language. Special attention is paid to concepts essential to writing basic computer programs. These concepts include: Data Types, Expressions, Loops, File Interaction, Collections, and Functions. Additionally, several tools required to develop Python applications will be explored. Throughout the course learners will develop increasingly complex applications as new topics are introduced.

Introduces topics and libraries related to data analytics in the Python programming language. Learners will explore reading, processing, and writing files in native Python. Then they will explore data analytics, processing and visualization using NumPy, Pandas, Matplotlib and Seaborn.

Introduces students to foundational concepts of data, information, and data management. Learners identify and use different types of data models. Learners use Microsoft Visio to create diagrams that illustrate how entities are related. Additional topics include eliminating data redundancy, explaining structures of relational tables, and compiling a data dictionary.

Learners describe primary keys and how to select them. Learners explain normalization and its role in the database design process. Learners apply normalization rules to evaluate and correct table structures. Learners use SQL Server and retrieve information from data tables. Learners use to SQL queries to join tables, aggregate data, and restrict data retrieval.

Create database models and database objects using T-SQL statements. Learners use data manipulation language (DML) to modify and create data. Learners manipulate the structure of existing tables to add, modify, and remove columns and constraints. Additional topics include foreign key relationships and indexes.

Students will apply problem solving techniques from discrete mathematics. Topics include symbolic logic, sets, algebra and base number systems.

Introduces learners to the basic concepts of using Microsoft Excel with hands-on, project based activities. Learners will develop foundational skills by applying concepts explored to effectively utilize the functions and features of Microsoft Excel including creating worksheets, entering/editing data, selecting cells/ranges, creating basic charts, formatting entries and creating/modifying basic formulas.

Develops writing skills which include prewriting, drafting, revising and editing. A variety of writing assignments are designed to help the learner analyze audience and purpose, research and organize ideas and format and design documents based on subject matter and content. Also develops critical reading and thinking skills through the analysis of a variety of written documents. Keywords: Written Comm, Comm, Writing

Learners develop and apply skills in all aspects of the writing process. Through a variety of learning activities and written documents, learners employ rhetorical strategies, plan, organize and revise content, apply critical reading strategies, locate and evaluate information, integrate and document sources, and apply standardized English language conventions.Keywords:English Comp, Comp 1, E Com, English 1, English

Introduces programming concepts and terminology using an object-oriented approach, with a focus on iterative development and testing. This course uses C# .NET, the Unified Modeling Language (UML) and other tools to present concepts from a variety of perspectives. Learners will create UML diagrams and write/debug C# .NET applications that incorporate classes, fields, methods and variables. Additional topics include: utilization of an Integrated Development Environment (IDE), value and reference types, object instantiation/lifetime/scope and mathematical/conditional/logical expressions.

Reinforces programming concepts and standards, building on the object-oriented approach introduced in 10-152-501 Programming Concepts A, with a focus on iterative development and testing. This course uses C# .NET, the Unified Modeling Language (UML) and other tools to present concepts from a variety of perspectives. Learners will create UML diagrams and write/debug C# .NET applications, applying the object-oriented basics of abstraction and encapsulation. Additional topics include: utilization of a debugger, object multiplicity and constructors.

Emphasizes programming concepts and standards, building on the object-oriented approach of 10-152-502 Programming Concepts B, with a focus on iterative development and testing. This course uses C# .NET, the Unified Modeling Language (UML) and other tools to present concepts from a variety of perspectives. Learners will create UML diagrams and write/debug C# .NET applications, applying the object-oriented basics of abstraction, encapsulation, inheritance.

Builds upon the basic database principles learned in Data Concepts, further exploring database design/normalization and introducing more complex and varied SQL statements. Learners will create/modify data objects and populate/retrieve data using SQL. Additional topics include: understanding constraints and keys on tables.

Builds on Database Design and SQL 1, learners use data manipulation language and data definition language to create and update more complex tables and data. Learners build views, indexes, and functions. Additional topics include database performance and SQL

Focus on error handling and database security. Learners engage with data from disparate sources in order to understand basics of extract, transform, load (ETL) procedures. Learners will build a database and move data from source to target and also build simple data reports to illustrate what is in the database.

Design charts, graphs, dashboards, and other visualizations with an understanding of color and chart type. Learners use the appropriate types of chart based on the data that is being presented and the audience that is viewing the presentation and also build charts for the purpose of exploratory data analysis.

Builds on Data Visualizations 1 and emphasizes choosing proper charts for quantitative and time-series analysis. Learners build effective dashboards and tell effective stories based on audience needs and analytical comfort. Learners contrast the ways in which data visualization can be used to tell truthful and untruthful stories.

Focuses on developing effective listening techniques and verbal and nonverbal communication skills through oral presentation, group activity, and other projects. The study of self, conflict, and cultural contexts will be explored, as well as their impact on communication.  Keywords: Oral, Oral Comm, Comm, Speech

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. Keywords: Stats, Intro to Stats, Data

Examines the intermediate level Microsoft Excel skills which build upon the basic Microsoft Excel concepts. Learners will demonstrate their ability to perform a number of hands-on, project based Excel intermediate level activities including but not limited to working with multiple worksheets and workbooks, creating, sorting and querying a table, importing data, working with SmartArt, images and screenshots, and financial functions.

Introduces learners to a variety of tools to upload data. Learners organize tables and databases through partitioning and creating backups. Learners use SQL tools to improve the performance of database tables. Additional topics include writing proper stored procedures and using SQL Server agents to schedule stored procedures.

Introduces learners to ETL (extract, transform, load) using SQL Server Data Tools. Learners use variables and parameters to write data to tables. Learners ensure that data is not duplicated or deleted when employing tools to load data to tables. Additional topics include scheduling ETL deployments.

Introduces learners to Business Intelligence tools and Cloud Storage. Learners distinguish between star and snowflake schema in order to leverage capacities in OLTP and BI systems. Learners create views and visualizations of data tables. Additional topics include use of Power BI, Amazon Web Services, and Google Cloud.

Introduces terminology, roles, and processes that are used in modern, successful project management. Learners design projects and work with project specific items including product backlogs, product owners, sprint planning, and scrum meetings. Learners compare and contrast project management strategies.

Employs RapidMiner, R, and Orange software packages in order to facilitate exploration of clustering, association, and text mining algorithms. Learners import a variety of data and use the algorithms in the various software products to extract meaningful information. Learners demonstrate their findings via PowerPoint and short video presentations.

This course provides a basic understanding of the theoretical foundations of ethical thought. Diverse ethical perspectives will be used to analyze and compare relevant issues. Students will critically evaluate individual, social and/or professional standards of behavior and apply a systematic decision-making process to these situations. Keywords: Ethics

Introduces the fundamental concepts and history of artificial intelligence (AI), including machine learning, neural networks, large language models and natural language processing. Students will explore AI technologies, review their development over time, and study their impact on society. This foundation will provide students with the necessary framework to understand and work with AI in future courses and professional settings.

Introduce learners to the foundational concepts of data programming in the open-source language R. Learners explore ways to visualize data, examine data structures, and model the relationship between variables using commands in R. Learners incorporate problem-solving and critical thinking skills as they write commands to support their work with data analysis.

Explores the relationship between the general principles of psychology and our everyday lives. Students are given the opportunity to achieve a deepened sense of awareness of themselves and others. This understanding enables students to improve their relationships with others at work, in the family and in society. Keywords: Psych, Relationships, Human Relations, Hr psych

This science of psychology course is a survey of multiple aspects of behavior and mental processes. It provides an overview of topics such as research methods, theoretical perspectives, learning, cognition, memory, motivation, emotions, personality, abnormal psychology, physiological factors, social influences, and development. Keywords: Psych, Intro to Psych

Applies all previous data analytics knowledge into one project. Learners perform (ETL) extraction, transformation, and loading of data. Learners query and analyze data. Learners create reports and visuals. Learners communicate results and findings to stakeholders.  

Employs RapidMiner, R, and Orange software packages in order to explore text mining using classification algorithms. Uses k-nearest neighbor and decision trees to further explore classification on structured data. Lastly, learners evaluate time series data using forecasting algorithms. Learners demonstrate their findings via PowerPoint and short video presentations.

Employs Python, Excel, R, and other GUI software to explore a variety of algorithms that fall under the umbrella of predictive analytics and data mining. Learners derive meaning from data using neural networks. Learners apply statistical models including linear and logistic regression. Lastly, learners evaluate data using Naïve Bayes and Bayesian Networks. Learners demonstrate their findings via PowerPoint and short video presentations.

This course is intended to develop analytic reasoning and the ability to solve quantitative problems. Topics to be covered may include: construction & interpretation of graphs; descriptive statistics; geometry & spatial visualizations; math of finance; functions and modeling; probability; and logic. Appropriate use of units and dimensions, estimates, mathematical notation, and available technology will be emphasized throughout the course.

Explores the use of AI in modern business environments, focusing on practical applications such as predictive analytics, customer relationship management, and automation. Students will analyze real-world case studies, assess the benefits and challenges of integrating AI into business operations, and explore AI-powered business tools and platforms.

Examines the ethical, legal, and societal implications of artificial intelligence (AI). Students will explore issues such as bias in algorithms, data privacy, and the broader impact of AI on employment and social structures and will utilize frameworks for ethical AI development and deployment, emphasizing responsible data-driven decision making.

Provides a comprehensive introduction to data engineering principles and foundational cloud computing for data. Students will learn to build and maintain scalable data pipelines, process and store large datasets, and implement cloud-based solutions for secure and efficient data management. With a focus on real-world applications, this course explores data ingestion, transformation, and storage strategies using AWS tools. By combining essential cloud computing skills with data engineering techniques, students will develop the expertise needed to support analytics, machine learning, and business intelligence workflows across diverse environments.

Examines the behavior of individual decision makers, primarily consumers and firms. Topics include choices of how much to consume and to produce, the functioning of perfectly and imperfectly competitive markets, the conditions under which markets may fail, and arguments for and against government intervention. The student applies the fundamental tools of economics to real world problems.