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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.
|1||DSI-505 or DSI-506||Programming I||None|
|2||DSI-507 or DSI-508||Programming II||Programming I|
|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|
|8||DSI-700||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.
|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|