Big Data and Machine Learning Concentration

Print Degree Planner (opens a new window) |

The Big Data and Machine Learning (BDML) program enables students to gain the technical skills that industry increasingly expects from data scientists. Big Data comes from the Internet of Things (IoT), robotics, autonomous vehicles, and other IT‐related fields such as scientific labs working with medical or remote‐sensing data, companies specializing in big data processing and analysis, cloud storage and computing services. These companies aggressively seek graduate‐level professionals who can 1) collect, clean, manage, analyze and interpret big data, 2) derive new knowledge from big data, 3) make sure these discoveries are transferred to the form of actionable items for upper administrators, and 4) clearly communicate to stakeholders through sophisticated but human‐friendly computer visualization techniques.

Degree Requirements

(Minimum of 34-36 hours)

Required Courses (12 Hours)

(to be taken in first term)

CSC 6780 - Fundamentals of Data Science 4 Credit Hours
CSC 6710 - Database Systems 4 Credit Hours
MATH 6751 - Mathematical Statistics I 3 Credit Hours
CSC 8902 - Ethics for Data Science 1 Credit Hours

Additional Required Courses (15 Hours)

CSC 6760 - Big Data Programming 4 Credit Hours
CSC 6740 - Data Mining 4 Credit Hours
CSC 6850 - Machine Learning 4 Credit Hours
MATH 6752 - Mathematical Statistics II 3 Credit Hours

Select One of the Following

STAT 8561 - Linear Statistical Analysis I 3 Credit Hours
STAT 8700 - Categorical Data Analysis 3 Credit Hours
STAT 8310 - Bayesian Data Analysis 3 Credit Hours

Select Two Courses from the Following (6-8 Hours)

(if not taken in areas 1 or 2 above)

CSC 8530 - Parallel Algorithms 4 Credit Hours
CSC 8710 - Deductive Databases and Logic Programming 4 Credit Hours
CSC 8711 - Databases and the Web 4 Credit Hours
CSC 8712 - Advanced Database Systems 4 Credit Hours
CSC 8713 - Spatial and Scientific Databases 4 Credit Hours
CSC 8740 - Advanced Data Mining 4 Credit Hours
CSC 8741 - Graph Mining 4 Credit Hours
CSC 8810 - Computational Intelligence 4 Credit Hours
CSC 8850 - Advanced Machine Learning 4 Credit Hours
CSC 8851 - Deep Learning 4 Credit Hours
CSC 8910 - Computer Science Topics Seminar 1 to 3 Credit Hours
STAT 8090 - Applied Multivariate Statistics 3 Credit Hours
STAT 8561 - Linear Statistical Analysis I 3 Credit Hours
STAT 8610 - Time Series Analysis 3 Credit Hours
STAT 8674 - Monte Carlo Methods 3 Credit Hours
CSC 8230 - Secure and Private Artificial Intelligence 4 Credit Hours
CSC 8852 - Advanced Topics of Deep Learning 4 Credit Hours

BDML Capstone Project (1 Hours)

DSCI 8390 - MS Project 1-4 Credit Hours

Graduate Assistants Requirements

Graduate assistants are required to enroll for a minimum of 20 credit hours each semester. These credit hours will consist of courses required for the prescribed program of study, as well as additional hours of CSC 8981 and CSC 8982.

CSC 8981 - Research in Computer Science 1 to 15 Credit Hours
CSC 8982 - Lab in Computer Science 1 to 15 Credit Hours