Core Courses

Stat 207 Statistical Inference for Data Science

Concepts in probability theory and sampling distributions; classical statistical inference; computational inference; principles of data science.

Prereq: Stat 100/equiv., Stat 195/equiv. 5 hours, 5 units

Stat 208 Programming for Data Analytics

Programming tools and methods for data analytics; modular and efficient programming; working with different data structures; high-performance programming; applications.

Prereq: Stat 210/equiv. 3 hours, 3 units

Stat 210 Statistical Software

Database management and programming using Statistical software.

3 hours, 3 units

Stat 217 Computational Statistics

Optimization methods; random numbers and Monte Carlo methods; Markov Chain Monte Carlo; resampling methods; recent approaches and methods in Computational Statistics.

Prereq: Stat 207/equiv.

Coreq: Stat 208/equiv. 3 hours, 3 units

Stat 218 Statistical Machine Learning

Applications of statistical machine learning; generalized linear models; supervised learning; unsupervised learning; kernel methods; support vector machines; neural networks; ensemble learning; contemporary topics.

Coreq: Stat 217/equiv. 6 hours, 6 units

Stat 227 Knowledge Discovery in Data

Frameworks and processes of knowledge discovery in data; data preprocessing; data exploration; data journalism and storytelling; ethics and privacy in data and analytics.

Coreq: Stat 218/equiv. 2 hours, 2 units

Stat 299 Special Project in Data Science

Integration and application of foundations, theories and methods of data analytics to address problems in industry, government, and other sectors; design and implementation of individual or group capstone project that is either project-oriented (engagement with and solution for a client) or research-oriented (work on own or client’s agenda)

must be taken during the last semester/term in the program, preferably after all core courses have been completed

4 hours, 4 units

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