(Restricted to MSMF and FSRM students)
Admission Requirements for Certificate
Students enrolled in the MSMF or FSRM degree programs who have completed their first year with a GPA of 3.0 or higher and have taken the prerequisite courses are eligible to earn the Certificate in Data Science. Most students can complete their degree program requirements within three semesters and students who wish to earn the certificate can complete the additional requirements by the end of their fourth semester. Students are required to complete the five courses designated for the certificate with grade B or higher.
Menu of Courses and Certificate Requirements
An MSMF student must complete any of the five required courses offered under MSDS Statistics track, or equivalent courses (approved by the managing committee). No CS courses are eligible for FSRM students and only CS 512 and CS 539 are eligible for MSMF students. Three of the five are in addition to the ten three-credit courses required by the MSMF degree program. The pre-requisites and syllabi of all courses are determined by the programs offering those courses.
Required: These two count as equivalent courses and towards the MSMF degree and Data Science Certificate.
- 16:220:607 Econometrics I
- 16:332:503 Programming Methodology for Numerical Computing and Finance (C++)
Choose at least three:
- Data Structures and Algorithms 16:198:512 (CS) [Fall]
- Database 16:198:539 (CS) [Spring]
- Data Wrangling and Husbandry 16:954:597 [Spring]
- Statistical Models and Computing 16:954:567 [Spring]
- Financial Data Mining and Machine Learning Methods 16:958:588 [Spring]
- Statistical Learning for Data Science 16:954:534 [Fall]
- Advanced Analytics Using Statistical Software 16:954:577 (Fall)
Certificate sample pathway
FSRM 1 Financial Statistics |
DS | FSRM 2 Risk Management |
DS | MSMF | DS Certificate |
|
Fall | ||||||
958:581 Prob & Inference |
Yes | 958:581 Prob & Inference |
Yes | 643:573 Numerical Anal.I |
||
958:563 Regression |
Yes | 958:563 Regression |
Yes | 643:621 Math Finance I |
||
958:590 Foundation Fin |
958:590 Foundation Fin |
220:607 Econometrics I |
Yes | |||
332:503 C++ Programming |
Yes | |||||
Spring | ||||||
958:565 Fin Time Series |
958:565 Financial Time Series |
643:574 Numerical Anal. II |
||||
958:535 Adv. Methods |
958:535 Adv. Methods |
643:622 Math Finance II |
||||
958:589 Adv. Programming |
958:589 Adv. Programming |
643:623 Computational Finance |
||||
958:588 Data Mining* |
* | 958:534 Advanced Risk Management |
220:508 Econometrics II |
|||
Fall | ||||||
954:534 Statistical Learning |
Yes Additional |
958:536 Advanced Risk Evaluation |
MSMF Elective | |||
958:587 Simulation |
958:587 Simulation |
958:588 Data Mining |
Yes Additional | |||
958:591 Algorithm Trading |
958:588 Data Mining |
Yes Additional |
954:577 Advanced Analytics Using Statistical Software or 198:512 Intro to Data Structure and Algorithms |
Yes Additional |
||
954:577 Software |
Yes Additional |
954:577 Software |
Yes Additional |
|||
Spring | ||||||
954:597 Data Wrangling |
Yes Additional |
954:597 Data Wrangling |
Yes Additional |
954:597 Data Wrangling or 198:539 Database |
Yes Additional | |
Elective | Elective | MSMF Elective |
Note: * take one semester earlier than the MS pathway.