MATH 403: Introduction to Discrete Mathematics
EECS 402: Programming for Scientists and Engineers
EECS 403: Data Structures for Scientists and Engineers
* 以下核心课程选一门：
BIOSTATS 601: Probability and Distribution
STATS 425: Introduction to Probability
STATS 510: Probability and Distribution
* 以下核心课程选一门：
BIOSTATS 602: Biostatistical Inference
STATS 426: Introduction to Theoretical Statistics
STATS 511: Statistical Inference
所有学生都必须选择以下选修课：
EECS 409: Data Science Colloquium
Expertise in Data Management and Manipulation
* 以下核心课程选一门：
EECS 484: Database Management Systems
EECS 584: Advanced Database Systems
* 以下核心课程选一门：
EECS 485: Web Systems
EECS 486: Information Retrieval and Web Search
EECS 549/SI 650: Information Retrieval
SI 618: Data Manipulation Analysis
STATS 507: Data Science Analytics using Python
Expertise in Data Science Techniques
* 以下核心课程选一门：
BIOSTAT 650: Applied Statistics I: Linear Regression
STATS 500: Statistical Learning I: Linear Regression
STATS 513: Regression and Data Analysis
* 以下核心课程选一门：
STATS 415: Data Mining and Statistical Learning
STATS 503: Statistical Learning II: Multivariate Analysis
EECS 505: Computational Data Science and ML
EECS 545: Machine Learning
EECS 476: Data Mining
EECS 576: Advanced Data Mining
SI 670: Applied Machine Learning
SI 671: Data Mining: Methods and Applications
BIOSTAT 626: Machine Learning for Health Sciences
Capstone
STATS 504: Principles and Practices in Effective Statistical Consulting
STATS 750: Directed Reading
EECS 598: Special Topics (Specific sections approved on a semesterly basis)
EECS 599: Directed Study
SI 691: Independent Study
SI 699-004: Big Data Analytics
BIOSTAT 610: Reading in Biostatistics
BIOSTAT 698: Modern Statistical Methods in Epidemiologic Studies
BIOSTAT 699: Analysis of Biostatistical Investigations
选修课：
* Principles of Data Science
BIOSTAT 601 (Probability and Distribution Theory)
BIOSTAT 602 (Biostatistical Inference)
BIOSTAT 617 (Sample Design)
BIOSTAT 626 (Machine Learning Methods)
BIOSTAT 680 (Stochastic Processes)
BIOSTAT 682 (Bayesian Analysis)
EECS 501 (Probability and Random Processes)
EECS 502 (Stochastic Processes)
EECS 545 (Machine Learning)
EECS 551 (Matrix Methods for Signal Processing, Data Analysis and Machine Learning)
EECS 553 (Theory and Practice of Data Compression)
EECS 559 (Optimization Methods for SIPML)
EECS 564 (Estimation, Filtering, and Detection)
SI 670 (Applied Machine Learning)
STATS 451 (Introduction to Bayesian Data Analysis)
STATS 470 (Introduction to Design of Experiments)
STATS 510 (Probability and Distribution Theory)
TATS 511 (Statistical Inference)
STATS 551 (Bayesian Modeling and Computation)
* Data Analysis
BIOSTAT 645 (Time series)
BIOSTAT 651 (Generalized Linear Models)
BIOSTAT 653 (Longitudinal Analysis)
BIOSTAT 665 (Population Genetics)
BIOSTAT 666 (Statistical Models and Numerical Methods in Human Genetics)
BIOSTAT 675 (Survival Analysis)
BIOSTAT 685 (Non-parametric statistics)
BIOSTAT 695 (Categorical Data)
BIOSTAT 696 (Spatial statistics)
EECS 556 (Image Processing)
EECS 659 (Adaptive Signal Processing)
STATS 414 (Topics in Applied Data Analysis
STATS 501 (Statistical Analysis of Correlated Data)
STATS 503 (Statistical Learning II: Multivariate Analysis)
STATS 509 (Statistics for Financial Data)
STATS 531 (Analysis of Time Series)
STATS 600 (Linear Models)
STATS 601 (Analysis of Multivariate and Categorical Data)
STATS 605 (Advanced Topics in Modeling and Data Analysis)
STATS 700 (Topics in Applied Statistics)
* Computation
BIOSTAT 615 (Statistical Computing)
BIOSTATS 625 (Computing with Big Data)
EECS 481 (Software Engineering)
EECS 485 (Web Systems)
EECS 486 (Information Retrieval and Web Search)
EECS 504 (Computer Vision)
EECS 542 (Advanced Topics in Computer Vision)
EECS 549/SI 650 (Information Retrieval)
EECS 548/SI 649 (Information Visualization)
EECS 572 (Randomness and Computation)
EECS 586 (Design and Analysis of Algorithms)
EECS 587 (Parallel Computing)
EECS 592 (Artificial Intelligence)
EECS 595/SI 561 (Natural Language Processing)
SI 608 (Networks)
SI 618 (Data Manipulation and Analysis
SI 630 (Natural Language Processing (Algorithms and People)
SI 671 (Data Mining: Methods and Applications)
STATS 406 (Computational Methods in Statistics and Data Science)
STATS 507 (Data Science Analytics using Python)
STATS 506 (Computational Methods and Tools in Statistics)
STATS 606 (Statistical Computing)
STATS 608 (Monte Carlo Methods and Optimization Methods in Statistics)
