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MS Minor in Data Science Analytics


​There is a new minor within the Biostatistics MS degree program in Data Science Analytics.

We offer this new minor in response to the changing landscape of biomedical research which is relying more and more on the generation, analysis and interpretation of large data sets.  With this new minor, students pursuing this training within the MS Biostatistics program will have an official designation within their degree, which will help with employment and other opportunities.

Eligibility

MS students and PhD students who are in the process of obtaining a MS degree are eligible.  It is best to plan out the minor starting the first year to ensure timely graduation and availability of electives.

Requirements

  • Take at least 8 credits of electives from a list of courses related to Data Science Analytics (see below).  There are additional elective credits required in the minor compared to the original MS degree, so that there is opportunity to specialize in this area.
  • Write a thesis or publishable paper with a focus on Data Science Analytics.

Timeline

The Biostatistics MS degree is designed to be completed in two academic years.  Although the minor requires additional credits for the specialization, the degree can still be completed within two years assuming students take courses over the summer.  See an example timeline below (individual cases and offerings every year will vary).

Year 1 Fall​

BIOS 6611 (3 credits)
BIOS 6631 (3 credits)
BIOS 6621 (1 credit)​
CSPH Required PH (1 credit)

Year 1 Spring​

​BIOS 6612 (3 credits)
BIOS 6632 (3 credits)
BIOS 6622 (1 credit)
MS Minor Elective (3 credits)

Year 1 Summer​

PUBH 6600 (2 credits)

Year 2 Fall​

BIOS 6623 (3 credits)
BIOS 6643 (3 credits)
MS Minor Elective (3 credits)

Year 2 Spring​

MS Minor Elective (3 credits)
EPID 6630 (3 credits)
MS Thesis/Research Paper (2 credits)

Year 2 Summer​

MS Thesis/Research Paper (2 credits)

List of currently accepted classes for electives:
Course Number Course Title Credits Course Director Delivery Method
BIOS 63101 Practical Clinical Informatics 3 Wiley Inclass - variable term & years
BIOS 66401 R for Data Science 2 Ghosh Inclass - variable term & years
BIOS 66421 Introduction to Python Programming 2 Zhang Inclass - variable term & years
BIOS 66441 Practical Data Wrangling 2 King Online - variable term & years
BIOS 66451 3 Predictive Analytics 3 Baron Inclass - variable term & years
BIOS 66801 Data Management Using SAS 3 Blatchford Inclass - every fall
BIOS 66811 Structured Query Language (SQL) 1 Blatchford Inclass - every summer
BIOS 66851 Intro Public Health Informatics 3 Moore Online - variable term & years
MATH 63881 3 Statistical and Machine Learning 3 Santorico/Hendricks Inclass – variable term & year
CSCI 4455/5455 Data Mining 3 Banaei-Kashani Inclass – variable term & year
CSCI 4580/5580 Data Science 3 Banaei-Kashani Inclass – variable term & year
CSCI 4930/5930 Machine Learning 3 Biswas Inclass – variable term & year
CSCI 4931/5931 Deep Learning 3 Biswas Inclass – variable term & year
CSCI 4951/5951 Big Data Systems 3 Banaei-Kashani Inclass – variable term & year
CSCI 5950/7950 Big Data Mining 3 Banaei-Kashani Inclass – variable term & year
CSCI 5952/7952 Big Data Science 3 Banaei-Kashani Inclass – variable term & year
23132 Object Oriented Programming 3 Various Inclass – fall/spring
CSCI 24212 Data Structures & Program Design 3 Various Inclass – fall/spring
32872 Database System Concepts 3 Various Inclass – fall/spring
CSCI 34122 Algorithms 3 Various Inclass – fall/spring


1
At least 3 BIOS credits should be taken

2Only one lower-level 2000/3000 CSCI course can count towards the electives, these are used to meet prerequisites of the 5000 CSCI series if needed
3Because of overlap, only MATH 6388 or BIOS 6645 can be counted as an elective

Your minor degree plan is subject to approval by the program director(s), please check with them before enrolling in minor electives

Not all courses above are offered every year, for academic year 2019-2020, here are the possible options:
Fall 2019
  • BIOS 6680 - Data Management Using SAS
  • BIOS 6640 - R for Data Science
  • BIOS 6644 - Practical Data Wrangling
  • CSCI 4931/5931 - Deep Learning
  • CSCI 5950 - Big Data Mining
  • CSCI 2312* - Object Oriented Programming
  • CSCI 2421* - Data Structures & Program Design (
  • CSCI 3287* - Database System Concepts
  • CSCI 3412* - Algorithms
Spring 2020
  • BSBT/BIOS 6310 - Practical Clinical Research Informatics
  • BIOS 6642 - Introduction to Python Programming
  • BIOS 6645 - Predictive Analytics
  • CSCI 4455/5455 - Data Mining
  • CSCI 5952 - Big Data Science
  • CSCI 4930/5930 - Machine Learning
  • CSCI 2312* - Object Oriented Programming
  • CSCI 2421* - Data Structures & Program Design
  • CSCI 3287* - Database System Concepts
  • CSCI 3412* - Algorithms

*only one lower-level 2000/3000 CSCI course can count towards the electives, these are used to meet prerequisites of the CSCI 5000 series if needed

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Mail Stop B119
Aurora, CO 80045


colorado.sph@ucdenver.edu

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