Skip to Main Content

This site provides information using PDF, visit this link to download the Adobe Acrobat Reader DC software.

Chat with TESU

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-5050 or DSI-5060 Programming I None
2 DSI-5070 or DSI-5080 Programming II Programming I
3 DSI-5300 Database Queries None
4 DSI-6010 or DSI-6040 Predictive Analytics I Programming I and II
5 DSI-6020 or DSI-6050 Predictive Analytics II Predictive Analytics I
6 DSI-6030 or DSI-6060 Predictive Analytics III Predictive Analytics II
7 DSI-6220 Data Visualization None
8 DSI-7000 Capstone All above courses

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-5090: Natural Language Processing I Core Python
DSI-6110: Natural Language Processing II None Either
DSI-6130: Anomaly Detection Core Either
DSI-5100: Forecasting Analytics None R
DSI-6140: Customer Analytics in R DSI-5060 R
DSI-6400: Spatial Statistics None R
DSI-5110: Network Analysis None Either
DSI-6080: R Programming Intermediate DSI-5060 and DSI-5080 R
DSI-6100: Optimization - Linear None Either
DSI-6250: Risk Simulation and Q None Either
DSI-6210: Integer and Nonlinear Programming DSI-6100 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."

Watch Toni »