16.4 Courses
16.4.1 Data Science Required Courses
Data Science
- DSCI 5001 Statistical Inference for Data Science (propaedeutic)
- DSCI 5002 Basics of Python and R (propaedeutic)
- DSCI 5003 Linear Algebra for Regression Analysis (propaedeutic)
- DSCI 6601 Practical Machine Learning
- DSCI 6602 Deep Learning and Artificial Intelligence
- DSCI 6607 Programmatic Data Analysis Using Python and R
- DSCI 6619 Regression Models (cross listed with STAT 6519)
- DSCI 6659 Statistical Exploration of Data (cross listed with STAT 6559)
- DSCI 6690 Data Science Case Study Series (2 credit hours)
- DSCI 695A/B Capstone Project (2 credit hours)
16.4.2 Data Science Elective Courses
Business
- BUSI 8025 Information Systems
- BUSI 9021 Data Management
- BUSI 9022 Information Systems Analysis and Design
- BUSI 9912 Probabilistic Models
Computer Science
- COMP 6907 Data Mining Techniques and Methodology
- COMP 6908 Database Technology and Applications
- COMP 6917 Complex Networks
- COMP 6934 Introduction to Data Visualization
Data Science
- DSCI 6650 Reinforcement Learning
Mathematics
- MATH 6100 Dynamical Systems
- MATH 6201 Numerical Methods for Time-Dependent Differential Equations
- MATH 6202 Nonlinear and Linear Optimisation
- MATH 6204 Iterative Methods in Numerical Linear Algebra
- MATH 6210 Numerical Solutions of Differential Equations
- MATH 6351 Advanced Linear Algebra
Medicine
- MED 6260 Applied Data Analysis for Clinical Epidemiology
- MED 6278 Advanced Biostatistics for Health Research
Scientific Computing
- CMSC 6950 Computer Based Tools and Applications
Statistics
- STAT 6503 Stochastic Processes
- STAT 6505 Survival Analysis
- STAT 6530 Longitudinal Data Analysis
- STAT 6545 Computational Statistics
- STAT 6561 Categorical Data Analysis
- STAT 6563 Sampling Theory
- STAT 6564 Experimental Designs
- STAT 6571 Financial and Environmental Time Series
- STAT 6573 Statistical Genetics
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