Data Science (B.S)

The bachelor of science degree in data science will provide necessary background in mathematics and build a strong foundation in data science, covering data structures, algorithms and database management, data collection, data mining, machine learning, modeling, and inference. 

Students graduating with a B.S. in Data Science will know how to develop software, design and maintain databases, process data in distributed environments, analyze the data using techniques from statistics, data mining and machine learning, provide visualizations of the data or the results of analysis, and assist decision makers. The program will include experiential learning via a capstone course, which will focus on applying the acquired knowledge and skills in a real-world data analytics project.

What you will learn
All graduates will be able to:

Develop software, algorithms; design and manage a variety of databases and structures, process data in distributed environments;
Collect and analyze the data using techniques from statistics, data mining, machine learning; 
Provide visualizations of the data and build statistical models to facilitate inference.
Interpret results of statistical analysis and assist decision makers

Course Requirements
The course requirements for the B.S. in Data Science are listed below. The coursework consists of at least 68 semester hours with 19 hours of Foundation (Area VI) and at least 49 hours of major coursework. 

C.1 Foundation Courses (Area VI, 19 credit hours)

• CSCI 1302 (4 hours) - Software Development
• CSCI 1360 (4 hours) - Foundations for Informatics and Data Analytics
• CSCI 2150 (4 hours) - Introduction to Computational Science
• CSCI 2720 (4 hours) – Data Structures
• STAT 2010 (3 hours) – Statistical Methods for Data Scientists 

C.2. Major Required Courses (at least 37 credit hours)

• CSCI 3360 (4 hours) - Data Science I
• CSCI 4260/6260 (4 hours) - Data Security and Privacy 
• CSCI 4360/6360 (4 hours) - Data Science II
• CSCI 4380/6380(4 hours) or STAT 4250 (3 hours) - Data Mining or Applied Multivariate Analysis and Statistical Learning 
• CSCI 4370/6370 (4 hours) - Data Base Management 
• MATH 3300 (3 hours) – Applied Linear Algebra
• STAT 4220 (3 hours) - Applied Experimental Designs
• STAT 4230/6230 (3 hours) - Applied Regression Analysis
• STAT 4510/6510 (3 hours) – Mathematical Statistics I
• STAT 4530 (3 hours) – Statistical Inferences for Data Scientists 
• STAT (CSCI) 4990 (3 hours) - Data Science Capstone 

C.3. Major Elective Courses (choose 12 hours from the list below)

• CSCI 3030 (3 hours) - Computing, Ethics, and Society
• CSCI 4050/6050 (4 hours) - Software Engineering
• CSCI 4150/6150(4 hours) - Numerical Simulations in Science and Engineering
• CSCI 4210/6210 (4 hours) - Simulation and Modeling
• CSCI 4470/64709(4 hours) - Algorithms
• CSCI 4850/6850 (4 hours) - Biomedical Image Analysis
• FINA 3001 (3 hours) – Financial Management
• MARK 3001 (3 hours) – Principles of Marketing
• MARK 4350 (3 hours) - Marketing Analytics 
• MARK 4650 (3 hours) – Digital Marketing Analytics 
• MATH (CSCI) 4690 (3 hours) - Graph Theory
• MATH 4600 (3 hours) – Probability         
• MGMT 3001 (3 hours) – Principles of Management
• MIST 5730 (3 hours) - Advanced Data Management 
• RMIN 4000 (3 hours) - Risk Management and Insurance
• STAT 4240/6240 (3 hours) - Sampling and Survey Methods
• STAT 4260/6260 (3 hours) - Statistical Quality Assurance
• STAT 4280/6280 (3 hours) - Applied Time Series Analysis
• STAT 42906290 (3 hours) - Nonparametric Methods
• STAT 4360/6360 (3 hours) – Statistical Software programming
• STAT 4620/6620 (3 hours) - Applied Categorical Data Analysis 
• STAT 4710/6710 (3 hours) - Introduction to Probability Theory I
• STAT 4720/6720 (3 hours) - Introduction to Probability Theory II

Employers:

• All graduates earning the B.S. in Data Science degree will learn the essential skills necessary to pursue careers in a variety of data-oriented companies [e.g., computing/internet companies (Google, Amazon, Facebook, IBM); engineering companies (Intel, Samsung, Boeing); finance/insurance (Goldman Sachs, AIG, Liberty Mutual); pharmaceutical companies (Johnson & Johnson)]; government/national labs (NASA, NIST, DoD) or pursue graduate studies.