The curriculum of the MSDA program has been updated in the sjsu.edu/msda catalog. The Department of Applied Data Science will offer courses only with DATA prefix starting fall 2020. For normal situation, each full-time student who has satisfied the admission conditions should follow the following programs of study path according to the admitted semester.
Fall 2019 Spring 2020 Fall 2020*
DATA 220 DATA 220 DATA 220
BUS 243 BUS 243 DATA 225
INFO 218 INFO 208 DATA 228
INFO 215 DATA 230 DATA 230
CMPE 257 DATA 245 DATA 245
DATA 294 DATA 294 DATA 294
DATA 240 DATA 240 DATA 240
DATA 255** DATA 255** DATA 255**
DATA 298A or 299A DATA 298A or 299A DATA 298A or 299A
DATA 298B or 299B DATA 298B or 299B DATA 298B or 299B
*due to COVID-19, the course offerings of semesters 3 and 4 will be updated for students admitted in Fall 2020.
**or DATA 250 if there is a sufficient demand.
MSDA students take this course during their second semester at SJSU. Silicon Valley domain experts and industry leaders are invited to the class to present their case studies and potential industry project topics for students. Students conduct independent research in applying data analytics to specific domains. Student also write effective technical reports and present results about emerging technologies in the area of data analytics in order to satisfy Graduate Writing Assessment Requirement (GWAR).
A new student must take at least one course during the first semester in order to keep his/her student status. An F-1 student must take 9-unit courses each, except the last, semester to keep the visa status.
Due to the course prerequisites, it is not practical to complete the MSDA program in less than 4 semesters. There is only one project (DATA 298B) or thesis (DATA 299B) class during the last semester.
There are no electives for students admitted to Fall 2018. However, students admitted to Fall 2019 can take 2 electives. All electives must be offered by the MSDA program. For the time being, MSDA program offers two electives – INFO 208 (Big Data Technologies) and CMPE 256 (Large Scale Analytics).