The Master of Science degree in Computational Data Science is a Purdue University degree offered in the Department of Computer and Information Sciences.
Data science is a cross between Computer Science and Statistics, and it involves data-driven knowledge discovery in terms of pattern analysis and prediction. You’ll study statistics, regression, sequence analysis, machine learning, data mining, and data analysis (like database systems, information visualization, and “big data” analytics).
Students graduate from this program ready to enter the workforce in the rapidly advancing field of data science, an interdisciplinary domain that cuts across computer science and statistics. You’ll gain the skills necessary to ensure you are competitive in today’s job market by gaining an understanding of theory, implementation (e.g., algorithms and appropriate computing languages), and the inherent “nature” of different data modalities, such as classification and prediction challenges on specific data (e.g., sparse and/or incomplete data).
Understanding the degree requirements
Students complete 30 credit hours in computer science and statistics courses at 500 level or above.
Core course requirement (9 credits in computer science, 6 credits in statistics)
- Computer Science
- CSCI 59000, Introduction to Data Science
- CSCI 57300, Data Mining
- CSCI 57800, Statistical Machine Learning
- STAT 51200, Applied Regression Analysis
- STAT 52900, Applied Decision Theory and Bayesian Analysis
Elective course requirement (12 credits total – 6 from computer science and 6 from statistics)
- Computer science
- CSCI 52000, Computational Methods in Analysis
- CSCI 54100, Database Systems
- CSCI 55200, Advanced Graphics & Visualization
- CSCI 58000 Algorithm Design, Analysis, and Implementation
- CSCI 59000, Large-scale Machine Learning
- CSCI 59000, High Performance Computing.
- STAT 51400 Design of Experiments
- STAT 52000 Time Series and Applications
- STAT 52300 Categorical Data Analysis
- STAT 52400, Applied Multivariate Analysis
- STAT 52501, Generalized Linear Models
- STAT 53600, Introduction to Survival Analysis
Capstone (3 credits)
- CSCI 69500, MS Capstone Project OR STAT 59800, Topics in Statistical Methods