Business Analytics, Advanced Certificate
Curriculum
Major Requirements
| Business Analytics | Credits: | |
| BUSA 701 | Data Interaction and Visualization | 3 |
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This course will provide students with understanding and proficiency in data interaction and visualization. This course will build on the concepts of business statistics and cover data visualization practices and tools for presenting big data. Students will learn effective data wrangling and visualization with Tableau and other relevant tools. They will also learn to design and develop interactive dashboards for deeper insights into the data. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| BUSA 705 | Predictive Analytics | 3 |
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Prerequisite: Prerequisites: QANT 630 The course provides the application of foundational topics for supervised learning algorithms such as Multiple Linear Regression, Logistics Regression, Nearest Neighbors, Decision and Regression Trees, Discriminant Analysis, Neural Networks, and Ensemble Methods. It first builds a sound understanding of data preparation, exploration, and reduction methods. This course covers prediction as well as classification processes. The emphasis is on learning the application of different machine learning techniques for decision-making situations across business domains rather than mastering the techniques' mathematical and computational foundations. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| MIST 725 | Database Systems | 3 |
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This is a prerequisite course for students in the Master's program in Data Science wo do not have a computer science background. This course covers various fundamental skills necessary for data science. Topics covered in this course include the Python programming language, relational databases and the SQL language, computer science basics, and command line interfaces. Classroom Hours - Laboratory and/or Studio Hours – Course Credits: 3-0-3 |
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| Total: 9 Credits | ||