Bachelor of Science in Data Analytics.
Course Overview
Data analytics allows companies to accurately know how the business is doing and enables insights for better decision making at the executive level. Data analytics encompasses a wide range of technologies to support analyzing business data, transforming information and generating intelligence. Technologies play important roles in the data analytics process and form the foundation of its architecture, and the need for employees who are knowledgable with such technologies and can perform analysis and help form analytically focused strategies continues to grow.
Course Structure
Required Courses:
STAT 1100 Descriptive Statistics (3 hours)
MATH 1360 Business Mathematics (3 hours)
CSIS 1500 Introduction to Business Technologies (3 hours)
CSIS 1700 Data Exploration (3 hours)
CSIS 2300 Electronic Commerce (3 hours)
CSIS 2500 Introduction to Data Science (3 hours)
CSIS 2800 Data Visualization Fundamentals (3 hours)
CSIS 3300 R Programming for Data Analytics (3 hours)
CSIS 3410 Information Analysis (3 hours)
CSIS 3700 Data Analytics Methods (3 hours)
CSIS 4300 Database Systems (3 hours)
CSIS 4310 Decision Support Systems (3 hours)
CSIS 4320 Data Warehousing (3 hours)
CSIS 4330 Machine Learning for Data Analytics (3 hours)
Elective Options:
A minimum of 120 credit hours consisting of the following:
42 required credit hours
Applicable University Global Citizenship Program hours
Elective credit hours
At least 21 of the required 42 credit hours must be taken at Webster University. All upper-level courses must be taken at Webster University.
Entry Requirement
| Admission Requirements | |
|---|---|
| Academic Entry Requirements | For Undergraduate Students:
For Graduate Students:
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| Language Requirement | |
|---|---|
| IELTS Score (Minimum) | 6.0 |
| TOEFL-IBT Score (Minimum) | 80 |