CSC 162: Data Structures and Algorithms in Python
DSCC 462: Computational Introduction to Statistics
DSCC 465: Introduction to Statistical Machine Learning (formerly Intermediate Statistical and Computational Methods)
DSCC 440: Data Mining
DSCC 461: Introduction to Databases (formerly Database Systems)
DSCC 483: Data Science Practicum
*选修课可以从以下领域选择
Computational methods
DSCC 401: Tools for Data Science (fall/spring)
DSCC 402: Data Science at Scale (spring)
DSCC 475: Time Series Analysis and Forecasting in Data Science (fall)
CSC 412: Human Computer Interaction (spring)
CSC 442: Artificial Intelligence (fall)
CSC 446: Machine Learning (spring)
CSC 444: Knowledge Representation and Reasoning in AI (fall)
CSC 447: Natural Language Processing (spring)
CSC 448: Statistical Speech and Language Processing (fall)
CSC 449: Machine Vision (spring)
CSC 452: Computer Organization (fall/spring)
CSC 458: Parallel and Distributed Systems (spring)
CSC 482: Design and Analysis of Efficient Algorithms (fall/spring)
CSC 486: Computational Complexity (spring)
CSC 576: Advanced Topics in Data Management
CSC 577: Advanced Topics in Computer Vision (spring)
CSC 578: Deep Learning (fall)
CSC 592: Mobile Visual Computing (fall)
CSSP 519: General Linear Approaches to Data Analysis II (spring)
BST 421W/STT 221W: Sampling Techniques (fall)
ECE 410/CSC 413/BCSC 570/BME 410/CVSC 534/NSCI 415/OPT 410-1 Introduction to Augmented and Virtual Reality (fall)
ECE 417: Introduction to Dip Using Python
ECE 477/CSC 464 Computer Audition (fall)
EESC 410: Stochastic Inverse Modeling in Geophysics (spring)
EESC 414: Earth Science Data Analysis (fall)
EESC 421: Quantitative Environmental Problem Solving
LING 424: Intro to Computational Liguistics (fall)
LING 450: Data Sciences for Linguistics
LING 470: Tools for Language Documentation
LING 481: Statistical and Neural Methods for Computational Linguistics (spring)
PHYS 573: Physics and Finance (fall)
Statistical methodology
STAT 416: Applied Statistical Methods-I (fall)
STAT 417: Applied Stat Methods II (spring)
STAT 418: Categorical Data Analysis (fall)
STAT 419: Nonparametric Inference (fall)
STAT 423: Bayesian Inference (spring)
STAT 476: Statistical Inference in R (spring)
STAT 477: Introduction to Statistical Software (fall)
ECE 440: Introduction to Random Processes (fall)
ECE 441: Detection Estimation Theory
ECE 442: Network Science Analytics (spring)
ECE 443: Probabilistic Models for Inference Estimation
PHYS 403: Data Science I: Modern Statistics and Exploration of Large Data Sets (spring)
PHYS 525: Data Science II: Complexity and Network Theory (fall)
Health and biomedical sciences
BIOL 453: Computational Biology (spring)
BIOL 457L: Applied Genomics with Lab (fall)
BST 432: High Dimensional Data Analysis (fall)
BST 433: Introduction to Computational Systems Biology
BST 434: Genomic Data Analysis (spring)
BST 467: Applied Statistics in the Biomedical Sciences (spring)
BCSC 547: Introduction to Computational Neurosciences
BCSC 512: Computational Methods in Cog Sci (every other fall)
BCSC 513: Introduction to fMRI
CSPS 504/BCSC 510: Data Analysis I
PM 410: Introduction to Data Management/Analysis (fall/spring)
PM 416: Epidemiologic Methods (spring)
PM 421: US Health Care System (fall)
PM 422: Quality of Care and Risk Adjustment (spring)
Business and Social Science*
Business and social science
CIS 417: Introduction to Business Analytics*
CIS 418: Advanced Business Modeling and Analytics*
CIS 432: Predictive Analytics/Python*
CIS 434: Social Media Analytics*
CIS 442F: Big Data*
FIN 418: Quantitative Finance w/ Python*
MKT 412: Marketing Research*
MKT 436R: Marketing Analytics using R*
MKT 440: Pricing Analytics*
MKT 437: Digital Marketing Strategy*
MKT 451: Advanced Quant Marketing *
PSCI 404: Probability and Inference (fall)
PSCI 405: Linear Models (spring)
PSCI 504: Causal Inference
PSCI 505: Maximum Likelihood Estimation
