Data Science (BS)

This program is offered by the George Herbert Walker School of Business & Technology/Computer and Information Sciences Department. It is available at the St. Louis main campus.

Program Description

The bachelor of science degree in data science is designed to address the core knowledge of data science field by focusing on required statistics, mathematics, computer science, and analytics to allow students to discover the fascinating world of data science. 

The program includes theoretical and practical applied approaches preparing students to enter the field of data science profession or continue their education in a professional graduate degree program. 

Learning Outcomes

Upon completion of the program, students will be able to:

• Demonstrate ability to explore data and identify the best statistical and mathematical model to apply for its analysis. 
• Demonstrate an ability to articulate, assess, and apply appropriate theories and principles of Machine Learning.  
• Develop and implement data analysis strategies based on theoretical principles, ethical considerations, and detailed knowledge of the underlying data.  
• Develop meaningful reports and visualization of data analytics appropriate to a technical and non-technical audience. 

Degree Requirements

For information on the general requirements for a degree, see Baccalaureate Degree Requirements under the Academic Policies and Information section of this catalog.

• 61 required credit hours
• Applicable University Global Citizenship Program hours
• Elective credit hours

At least 40 of the required 61 credit hours must be taken at Webster University. All upper-level (3000 and above) courses must be taken at Webster University.

Required Courses

• COSC 1550 Computer Programming I (3 hours)
• CSIS 1700 Data Exploration (3 hours)
• COSC 1800 Python Programming (3 hours)
• MATH 1610 Calculus I (5 hours)
• MATH 1620 Calculus II (5 hours)
• MATH 2200 Statistics (3 hours)
• MATH 2410 Discrete Mathematics (3 hours)
• CSIS 2500 Introductions to Data Science (3 hours)
• CSIS 2700 Data Privacy, Security, and Ethics (3 hours)
• MATH 3160 Linear Algebra (3 hours)
• CSIS 3300 R Programming for Data Analytics (3 hours)
• CSIS 3410 Information Analysis (3 hours)
• MATH 3610 Probability (3 hours)
• CSIS 3700 Data Analytics Methods (3 hours)
• CSIS 4300 Database Systems (3 hours)
• COSC 4310 Database Programming (3 hours)
• CSIS 4330 Data Mining (3 hours)
• CSIS 3800 Machine Learning (3 hours)
• CSIS 4500 Data Science Capstone (3 hours)