Data Analytics - Associate Degree

Students gain skills that lead to success in college, employment, and life. Students should take this course in their first semester. (Pre-requisite: None.)

Learners develop knowledge/skills in planning, organizing, writing, editing. Students will also analyze audience/purpose, use elements of research, format documents using standard guidelines, and develop critical reading skills. (Prerequisite: GPA greater/equal to 2.6; OR ACT Reading score greater/equal to 15 AND English greater/equal to 18; OR Next Gen Reading score greater/equal to 250 AND Writing score greater/equal to 250; OR "preparatory course(s)", contact academic advisor at 920-498-5444)

This course is intended to develop analytic reasoning and the ability to solve quantitative problems. Topics include logic, probability, descriptive and inferential statistics, linear and non-linear modeling, graphical representation, and functions.  The course emphasizes appropriate use of units, dimensions, estimates, mathematical notation, and technology. (Prerequisite: GPA greater/equal to 2.6; OR Next Gen QRAS score greater/equal to 250 AND Rdg score greater/equal to 250; OR ACT Math score greater/equal to 21 AND ACT Reading score greater/equal to 15-contact an academic advisor 920-498-5444).

Creating worksheets; enter data, make modifications, work with formulas and functions, create and enhance charts, manage data, transform data, conditional formatting, importing/exporting data, introduction to PivotTables and PivotCharts.

This course provides an overview of the interconnectedness among careers within Information Technology. Learn how various fields within the broader industry each play an integral role and how a personal brand fits into preparing you for your career choice.  (Corequisite: 10-890-101, College 101)

Learners will develop an understanding of cybersecurity methods, terms, and key technical concepts to identify and protect assets against attacks.

Covers working with data tools, advanced formatting techniques, advanced functions, evaluating formulas, collaboration tools, data validation, form controls, macros, working with templates, and collaborating with multiple Excel users. (Pre-req: 10-103-131, MS Excel Intro)

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. (Prerequisite: GPA greater/equal to 2.6 AND C or better in Algebra II or equivalent; OR Next Gen QRAS greater/equal to 250 AND Rdg greater/equal to 250; OR ACT Math greater/equal to 24 AND ACT Rdg greater/equal to 15; OR "C" or better in Inter Alg or higher-contact academic advisor 920-498-5444).

Power BI (Business Intelligence). This course provides an introduction and exploration of business analysis tools utilized in connecting, aggregating, and visualizing data from multiple sources to quickly summarize data. You will learn how to extract, transform, and load data, build a data model using modeling features, creating proper relationships, and design considerations. (Prerequisite: 10-103-132, MS Excel Part 2 or you are accepted into the Data Analytics Visualization Certificate)

Database uses, database terminology, analyzing information requirements, data models, database design phases, entity relationships, normalization processes, database management systems, database objects, development environments, creating tables, writing queries using SQL, testing.

Instruction in the multiple approaches used for performing business analysis, planning activities and ongoing communication, defining scopes, process improvements, assumptions, constraints, and dependencies, and the management process.

The role of project management, developing a project proposal, demonstration of relevant software, working with project teams, sequencing tasks, charting progress, dealing with variations, budgets and resources, implementation, and assessment.

Investigate the fundamentals of computer programming using the Python programming language. Students examine data types, variables, conditional statements, looping, array structures, and structured programming techniques. Upon completion of the course, students will be able to use Python to apply problem solving skills to create applications for delivery to various platforms.

In this course, students will learn to organize, manage, and analyze very large data sets from various sources. Students will use software tools to present complex data in visually meaningful representations that can be communicated to business stakeholders. Upon completion, students will learn how to transform raw data into meaningful information that will be utilized for data-driven decision making. (Prerequisite: 10-103-175, Power BI with a "C" or better)

Write queries in a relational database: creating tables, setting primary/foreign keys, populating tables, manipulating data and reporting. Explore join types, stored procedures, functions, and database administration SQL statements. (Prerequisite: 10-152-125, Database Design with a "C" or better)

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. (Prerequisite: 10-804-189, Introductory Statistics with a "C" or better)

Will provide business analysis and make focused organizational decisions by mining, aggregating, and conducting descriptive, prescriptive, and predictive analytics on big data using a variety of analytic tools.

Create professional resume and cover letter, prepare for interviews, understand interviewing techniques, participate in a mock interview, evaluate outcomes of interview, and prepare for Career Experience. (Prerequisites: 10-105-100, Careers in Business OR 10-107-117, Careers in IT OR 10-201-100, Careers In Digital Arts)

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. (Prerequisite: GPA greater/equal to 2.6; OR Next Gen Rdg score greater/equal to 250 AND Writing score greater/equal to 237; OR ACT Rdg score greater/equal to 15 AND English greater/equal to 15; OR 10-831-107, College Reading and Writing with a B or better)

Explore the process of evaluating alternative courses of action to given problems and arriving at the most suitable plan. Operational decision making requires thorough analysis of the pros and cons of every alternative solution. Explore features of production/service systems to include aggregate planning, forecasting techniques, scheduling, MRP and ERP, and inventory management systems. An operational simulation will apply the learnings.

This course introduces students to lean principles in manufacturing and operations within a Just-In-Time (JIT) framework. Topics include productivity systems, quality management, statistical process control, 5S, Kaizen, Kanban, value stream mapping, and production logistics. Emphasis is placed on continuous improvement tools and the integration of human resources in lean environments.

This course is designed to give an overview of how a market-oriented economic system operates, and it surveys the factors which influence national economic policy. Basic concepts and analyses are illustrated by reference to a variety of contemporary problems and public policy issues. Concepts include scarcity, resources, alternative economic systems, growth, supply and demand, monetary and fiscal policy, inflation, unemployment and global economic issues. (Prerequisite: GPA greater/equal to 2.6; OR Next Gen Rdg score greater/equal to 250 AND Writing score greater/equal to 237; OR ACT Rdg score greater/equal to 15 AND English greater/equal to 15; OR 10-831-107, College Reading and Writing with a B or better.)

Gain a solid foundation in Lean Six Sigma principles and tools while preparing for Green Belt certification. This course introduces the core concepts of Lean and Six Sigma, explaining their importance in driving continuous improvement and operational excellence. You'll explore key terminology, strategies for successful implementation, and the Define-Measure-Analyze-Improve-Control (DMAIC) methodology. By the end of the course, you'll be equipped with the knowledge and skills needed to pursue Green Belt certification and lead data-driven process improvement initiatives. (Prerequisite: 10-182-117 Principles of Lean Operations)

This course 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. (Prerequisite: GPA greater/equal to 2.6; OR Next Gen Rdg score greater/equal to 250 AND Writing score greater/equal to 237; OR ACT Rdg score greater/equal to 15 AND English score greater/equal to 15; OR preparatory course-contact an academic advisor at 920-498-5444)

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. (Prerequisite: 10-156-114, Data Analytics with a "C" or better)

Students can select any hands-on experience related to: Internship, Field Research, Service Learning, Simulations, Capstone, Industry Related, or International. Instructor approval required. (Prerequisite:10-105-103, Career Fundamentals)