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2021 - 2022 Academic Catalog

Data Analytics

The Data Analytics minor consists of six courses.

Course Code Course Title Credits
Core Courses
DSCI102 Introduction to Computer Science 3
DSCI105 Data Warehouse and Business Intelligence 3
DSCI202 Business Analytics 3
Choose 1 from the following
MATH208 Statistics 3
MATH209 Business Statistics 3
Choose 2 from the following:
DSCI201 Analytics using SAS Visual Analytics 3
DSCI204 How to Think Like a Data Scientist 3
MATH305 Advanced Statistics 3


Credit Requirements for minor: 18 credits

DSCI102 - Introduction to Computer Science

This introduction to computer science, emphasizes problem solving and data analysis skills along with computer programming skills. Using Python, students learn design, implementation, testing, and analysis of algorithms and programs. And within the context of programming, they will learn to formulate problems, think creatively about solutions, and express those solutions clearly and accurately. Problems will be chosen from real-world examples such as graphics, image processing, cryptography, data analysis, astronomy, video games, and environmental simulation. Students get instruction from a world-class computer science professor, delivered remotely through video and interactive media and attend class for collaborative team projects to solve real-life problems. Prior programming experience is not a requirement for this course. Formerly: INTC102

DSCI105 - Data Warehouse and Business Intelligence

This course begins with the introduction of a data warehouse. Students will learn the concepts, tools and application of data warehouse for business reporting and online analytical processing. Students will also learn how to create visualizations and dashboards, and descriptive analytics. The material builds from the concepts learned in basic statistics courses. Core tools used in this course include Microsoft Excel, and SAS Visual Analytics. Excel will be used to teach the basics of visualizations – like bar charts, line charts etc. in order to ramp-up the students’ expertise into SAS Visual Analytics. SAS Visual Analytics will be used as a tool to introduce students to data warehousing, and building basic visualizations. Students will also be exposed to Facts and Dimensions.

DSCI202 - Business Analytics

This course provides the conceptual and technical foundations of various aspects of Data Analytics. The purpose is to prepare students with foundation skills in Big Data, a skill widely needed and valued across the business world. The course will expose students to the data analytics practices executed in the business world and explores key areas of the analytical process, how data is created, stored, accessed, and how organizations work with data and creates the environment in which analytics can flourish. This course will provide students with a strong foundation in all the areas that support analytics and will help them to better position themselves for success within any organization. This course provides the conceptual and technical foundations of various aspects of Big Data Analytics, including cloud computing, NoSQL Databases, predictive and prescriptive analytics. Prerequisite: MATH208 or MATH209.

MATH208 - Statistics

This is an introductory course in descriptive and inferential statistics. Topics include: data analysis, and graphical methods of describing data, measures of central tendency and variability, probability, the normal distribution, sampling distributions, confidence intervals, hypothesis testing, correlation, and regression analysis. Prerequisites: MATH 106 with a grade of C or better or demonstrated competency through placement testing and ENG 102.

MATH209 - Business Statistics

This is an introductory course in descriptive and inferential statistics focused on applications in business. Topics include: data analysis, and graphical methods of describing data, measures of central tendency and variability, time-series analysis, trend and seasonality analysis, simple and multiple correlation and regression analysis, sales and cost forecasting, probability, expected monetary value, and the Normal distribution. Prerequisites: MATH 106 with a grade of C or better or demonstrated competency through placement testing and ENG 102. With permission of the instructor only.

DSCI201 - Analytics using SAS Visual Analytics

This course focuses on building and enhancing skills from the Data Warehousing and Business Intelligence course. Students will expand their concepts of Business Intelligence, Visualizations, Dashboards, and Descriptive Analytics. The core tool used in this course is SAS Visual Analytics. Students will create visualizations, dashboards, and export reports to be able to present to the class. Prerequisite: DSCI105.

DSCI204 - How to Think Like a Data Scientist

This course introduces students to the importance of gathering, cleaning, normalizing, visualizing and analyzing data to drive informed decision-making, no matter the field of study. Students will learn to use a combination of tools and techniques, including spreadsheets, SQL and Python to work on real-world data sets using a combination of procedural and basic machine learning algorithms. They will also learn to ask good, exploratory questions and develop metrics to come up with a well-thought-out analysis. Presenting and discussing an analysis of data sets chosen by the students will be an important part of the course. Prerequisites: DSCI102 and DSIC103 (formerly INTC102/103).

MATH305 - Advanced Statistics

Quantitative statistical tools for modern data analysis are used across a range of disciplines and industries to guide organizational, societal and scientific advances. Using data sets from across a variety of fields, the focus will be on applications and analysis. Topics include two sample confidence intervals, Chi Square tests, multiple regression analysis, ANOVA, non- parametric tests, sampling, and simulation. Prerequisite: Math 208 or Math 209