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MS in Data Science and Analytics Course Sequencing and Schedule
The MS in Data Science and Analytics program follows a curricular structure that is sequential.  Much of the coursework in this program builds upon knowledge gained in previous courses in the sequence.  Students are advised to enroll in required coursework following the below sequence.


Sequence
Course Description Advisement

1

DSI-505 or DSI-506 Programming 1 None

2

DSI-507 or DSI-508 Programming 2 Programming 1

3

DSI-530 Database Queries None

4

DSI-601 or DSI-604 Predictive Analytics 1 Programming 1 & 2

5

DSI-602 or DSI-605 Predictive Analytics 2 Predictive Analytics 1

6

DSI-603 or DSI-606 Predictive Analytics 3 Predictive Analytics 2

7

DSI-622 Data Visualization None

8

DSI-700 Capstone All above courses

Electives
Some electives in this program are sequential and carry an advisory that students complete specific coursework prior to enrolling.  Some electives in this program are specific to the track a student chooses (R or Python).  The “core” refers to the required programming and predictive analytics courses in the above sequence.


Course
Description Advisement Track
DSI-509 Text Mining Core Python
DSI-611 NLP None Either
DSI-612 Deep Learning Core Python
DSI-613 Anomaly Detection Core Either
DSI-510 Forecasting Analytics None R
DSI-614 Customer Analytics in R DSI-506 R
DSI-640 Spatial Statistics None R
DSI-511 Network Analysis None Either
DSI-608 R Programming Intermediate DSI-506 & DSI-508 R
DSI-610 Optimization - Linear None Either
DSI-625 Risk Simulation and Q None Either
DSI-621 Integer and Nonlinear Programming DSI-610 Either

Toni M. Terry, BA

"I am 67 years old, soon to be 68, and to be able to say I did this at this day in my life is just gratification for my own self."

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