Bachelor of Applied Science in Data Analytics
George Mason University
Key Information
Campus location
Fairfax, USA
Languages
English
Study format
On-Campus
Duration
4 years
Pace
Full time
Tuition fees
USD 4,897 / per semester *
Application deadline
01 Jun 2024
Earliest start date
Aug 2024
* in-state tuition full-time (12-15 credits); USD 16,980 - out-of-state tuition full-time (12-15 credits); USD 1,803 - mandatory student fee
Introduction
Offered in collaboration with the College of Computing and College of Science, the Data Analytics concentration is designed for students who hold an Associate of Applied Science (AAS) degree in a technology-related field.
This concentration is designed to provide students with an understanding of the technologies and methodologies necessary for data-driven decision-making. It is aimed at students who wish to become data scientists and analysts in finance, marketing, operations, business/government intelligence, and other information-intensive groups generating and consuming large amounts of data.
Curriculum
Degree Requirements
Total credits: 120-126
In addition to satisfying all Mason Core requirements, students must satisfy the requirements for one of the eight concentrations.
This concentration is in collaboration with the College of Engineering and Computing. Full admissions requirements can be viewed on the program website.
Students must have a C or better in any course that satisfies a prerequisite for an IT course. To graduate with the BAS with a Data Analytics concentration, students must have a C or better in their core, concentration, and applied for coursework courses.
Core Requirements
- BAS 300 Building Professional Competencies 3
- BAS 490 Introduction to Research Methods 3
- BAS 491 Applied Sciences Capstone (Mason Core) 3
Concentration Requirements
- MATH 108 Introductory Calculus with Business Applications (Mason Core) 3 or MATH 113 Analytic Geometry and Calculus I (Mason Core)
- STAT 250 Introductory Statistics I (Mason Core) 3
- STAT 350 Introductory Statistics II 3
- STAT 362 Introduction to Computer Statistical Packages 3
- STAT 463 Introduction to Exploratory Data Analysis 3
- IT 102 Discrete Structures 3
- IT 109 Introduction to Computer Programming 3 or IT 106 Introduction to IT Problem Solving Using Computer Programming
- IT 209 Introduction to Object Oriented Programming 3 or IT 206 Object Oriented Techniques for IT Problem Solving
- IT 309 Data Structures and Algorithms in Python 3 or IT 306 Data Structures and Algorithms in Java
- IT 343 IT Project Management 3
Applied Coursework
Select 9 credit hours of applied coursework from the following. Courses not listed may be selected in consultation with the advisor.
- CDS 301 Scientific Information and Data Visualization
- CDS 302 Scientific Data and Databases
- CDS 303 Scientific Data Mining
- STAT 455 Experimental Design
- STAT 456 Applied Regression Analysis
- STAT 460 Introduction to Biostatistics
- STAT 462 Applied Multivariate Statistics
- STAT 465 Nonparametric Statistics and Categorical Data Analysis
- STAT 474 Introduction to Survey Sampling
- SYST 469 Human-Computer Interaction