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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 I None
2 DSI-507 or DSI-508 Programming II Programming I
3 DSI-530 Database Queries None
4 DSI-601 or DSI-604 Predictive Analytics I Programming I and II
5 DSI-602 or DSI-605 Predictive Analytics II Predictive Analytics I
6 DSI-603 or DSI-606 Predictive Analytics III Predictive Analytics II
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 Advisement Track
DSI-509: Natural Language Processing I Core Python
DSI-611: Natural Language Processing II None Either
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 and 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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