# Data Science Pathway

The Biostatistics data science pathway combines rigorous statistical training with the development of advanced computational skills to solve the public health challenges of tomorrow. Required courses cover epidemiology, regression models, databases, machine learning and more. Students will become familiar with data science programming tools (e.g. R, Python, SQL and NoSQL databases). Data science pathway graduates can find careers analyzing large volumes of health data in government (e.g. public health agencies), hospitals, industry (e.g. pharmaceutical companies) or research.

Students pursuing this pathway will graduate with the key skills of any Biostatistician. Unlike the traditional pathway, data science pathway students will have more experience using computational techniques to store, manipulate and analyze large volumes and varieties of data. This pathway trains biostatisticians; as such, it emphasizes the development and application of rigorous statistical theory to extensive health data sets, as opposed to application of the latest computational techniques that are prioritized in the health informatics masters. The focus on health applications differentiates this pathway from the MS in Data Science and Statistics.

Students must choose this pathway at the start of their two-year program.

## Requirements - Data Science Pathway

### MS Required Courses (10 course units)

- BIS 525 Seminar in Biostatistics and Journal Club - 0 units
- BIS 526 Seminar in Biostatistics and Journal Club - 0 units
- BIS 620 Data Science Software Systems - 1 unit
- BIS 623 Advanced Regression Models [or S&DS 612 Linear Models] - 1 unit
- BIS 628 Longitudinal and Multilevel Data Analysis - 1 unit
- BIS 630 Applied Survival Analysis [or BIS 643 Theory of Survival Analysis] - 1 unit
- BIS 678 Statistical Practice – Capstone Experience - 1 Unit
- BIS 687 Data Science Statistical Practice- Capstone Experience - 1 unit
- EPH 508 Foundations of Epidemiology and Public Health - 1 unit
- EPH 608 Frontiers of Public Health * - 1 unit
- EPH 600 Research Ethics and Responsibilities - 0 units
- S&DS 541 Probability Theory [or S&DS 600 Advanced Probability or S&DS 551 Stochastic Process] - 1 unit
- S&DS 542 Theory of Statistics [or S&DS 610 Statistical Inference] - 1 unit
- BIS 695 Summer Internship in Biostatistical Research - 0 units
- EPH 100/101 Professional Skills Series - 0 units

### MS Electives in Biostatistics (minimum 2 course units)

- BIS 555 Machine Learning and Biomedical Data - 1 unit
- BIS 557 Computational Statistics - 1 unit
- BIS 634 Computational Methods for Informatics - 1 unit
- BIS 646 Nonparametric Statistical Methods and their Applications - 1 unit

### Electives in Machine Learning (1 course unit)

- BIS 555 Machine Learning and Biomedical Data - 1 unit
- BIS 557 Computational Statistics - 1 unit
- BIS 634 Computational Methods for Informatics - 1 unit
- BIS 646 Nonparametric Statistical Methods and their Applications - 1 unit
- S&DS 565 Introductory Machine Learning - 1 unit
- S&DS 563 Multivariate Statistical Methods for the Social Sciences - 1 unit
- S&DS 631 Optimization and Computation – 1 unit
- CB&B 555 Unsupervised Learning for Big Data - 1 unit
- CB&B 567 Topics in Deep Learning: Methods & Biomedical Applications - 1 unit
- CB&B 663 Deep Learning Theory and Applications - 1 unit
- CB&B 745 Advanced Topics in Machine Learning - 1 unit

### Electives in Databases (1 course unit)

- BIS 638 Clinical Database Management Systems and Ontologie - 1 unit
- CPSC 537 Introduction to Database Systems - 1 unit

### Electives (2 course units)

### Other Courses

- BIS 649/BIS 650 Master’s Thesis Research - 2 units

Students choosing this option must present their research in a public seminar to graduate

*Students entering the program with an MPH or relevant graduate degree may be exempt from this requirement.

Students should take no more than 5 courses for credit each semester (BIS 525/526, EPH 600, EPH 100/101 are not for credit). Courses listed without a notation in the “term taken” column can be taken in either year of the program if prerequisites are met and with advisor approval.

*rev. 7.28.2021*