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Course Descriptions

BAS-120: Introduction to Analytics

This course introduces basic concepts and applications of analytics. Topics include an overview of the analytical process and the role of the analyst, applied descriptive statistics, and exploratory data analysis. Upon completion, students should be able to demonstrate a basic understanding of analytics for decision-making in business.

Course Prerequisites:
Take 1 group; Option: Take ENG-002; Option: Take ENG-025; Option: Take ENG-110(S26392); Take previously. Required.Take 1 group; Option: Take MAT-003; Option: Take MAT-025; Option: Take MAT-035; Option: Take MAT-110(S26398); Take previously. Required.
Total Credits:3
Class Credits:2
Lab Credits:3
Clinic Credits:0

BAS-121: Data Visualization

This course introduces key concepts in data visualization and reporting. Topics include concepts and methods used in graphical representation of data, exploration and reporting of data, and basic linear regression methods. Upon completion, students should be able to effectively use graphical tools to communicate insights about data.

Course Prerequisites:
Take BAS-120(S24318); Take previously. Required.
Total Credits:3
Class Credits:2
Lab Credits:3
Clinic Credits:0

BAS-150: Introduction to Analytical Programming

This course introduces statistical software for analytics. Topics include utilization of analytical and statistical software packages for data management, data visualization, and exploratory data analysis. Upon completion, students should be able to use statistical programming tools to conduct descriptive analytics.

Course Prerequisites:
Take 1 group; Option: Take ENG-002; Option: Take ENG-025; Option: Take ENG-110(S26392); Take previously. Required.Take 1 group; Option: Take MAT-003; Option: Take MAT-025; Option: Take MAT-035; Option: Take MAT-110(S26398); Take previously. Required.
Total Credits:3
Class Credits:2
Lab Credits:3
Clinic Credits:0

BAS-220: Applied Analytical Programming

This course covers applications of statistical software for data management and reporting. Topics include data management, data preprocessing, and modeling including linear and logistic regression analysis using programming tools. Upon completion, students should be able to process data and generate reports that support business decision-making.

Course Prerequisites:
Take BAS-150(S24320); Take previously. Required.
Total Credits:3
Class Credits:2
Lab Credits:3
Clinic Credits:0

BAS-221: Introduction to Predictive Analytics

This course introduces foundations of predictive analytics. Topics include basic predictive modeling methods for both classification and regression tasks. Upon completion, students should be able to build and validate predictive models.

Course Prerequisites:
Take BAS-121(S24319) BAS-220(S24321); Take previously. Required.
Total Credits:3
Class Credits:2
Lab Credits:3
Clinic Credits:0

BAS-230: Applied Predictive Modeling

This course covers advanced applications of predictive models. Topics include the advanced use of classification and regression models in real-world scenarios. Upon completion, students should be able to utilize their knowledge and skills in predictive analytics to independently guide decision makers.

Course Prerequisites:
Take BAS-221(S24322); Take previously. Required.
Total Credits:3
Class Credits:2
Lab Credits:3
Clinic Credits:0

BAS-240: Data Structures for Analytics

This course is designed to enhance student proficiency in data management skills for analytics applications. Topics include techniques and methods for identification, extraction, and preparation of data for processing with analytical software. Upon completion, students should be able to demonstrate the skills necessary to effectively organize and combine different data sources for analytic applications.

Course Prerequisites:
Take BAS-121(S24319) BAS-220(S24321); Take previously. Required.
Total Credits:3
Class Credits:2
Lab Credits:3
Clinic Credits:0

BAS-250: Analytical Tools and Methods

This course covers advanced statistical and analytic tools for use in decision-making. Topics include an overview of data mining, unsupervised machine learning techniques, analysis of semi-structured and unstructured data, and text analytics. Upon completion, students should be able to analyze complex data with modern analytical tools and methods.

Course Prerequisites:
Take BAS-240; Take previously. Required.Take BAS-230(S24323); Take previously. Required.
Total Credits:3
Class Credits:2
Lab Credits:3
Clinic Credits:0

BAS-270: Advanced Analytical Tools and Methods

This course covers the planning and execution of an analytics project that integrates the analytical knowledge and skills acquired through prior coursework. Students will define and carry out an analytics project from inception to final reporting. Upon completion, students should be able to demonstrate their ability to apply analytic methods and best practices in a simulated business setting.

Course Prerequisites:
Take BAS-221(S24322) BAS-240; Take previously. Required.Take BAS-250(S24331); Take previously. Required.
Total Credits:3
Class Credits:2
Lab Credits:3
Clinic Credits:0
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