Concentrations
MSFE students are able to select a concentration area within the MSFE degree. These concentration courses also meet the electives for the program and can be considered beginning with the 2nd semester of the program. In order to obtain a concentration, the prescribed courses must be met as listed below. To officially declare a concentration on your transcript, you must contact your program advisor.
The official department concentration requirements are listed on the University Academic Catalog.
Please note: Not all courses are available each semester. Please refer to the Course Catalog for course availability for each term.
*MSFE required courses are listed in bold.
|
Data Analytics -Finance (DA-FIN) |
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| Course | Course Title | Credit Hours |
| Required: | ||
| FIN 550 | Big Data Analytics in Finance for Predictive and Causal Analysis | 4 |
| and any two of the following graduate courses: | ||
| FIN 552 | Applied Financial Econometrics | 4 |
| FIN 553 | Machine Learning in Finance | 4 |
| FIN 555 | Financial Innovation | 4 |
| FIN 537 | Financial Risk Management | 4 |
| FIN 580 | Financial Data Management & Analysis | 4 |
| FIN 580 | Quantamental Investment | 4 |
| Hours needed to satisfy the concentration: | 12 | |
|
Advanced Analytics -Industrial & Enterprise Systems Eng. (AA-ISE) |
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| Course | Course Title | Credit Hours |
| Required: (choose 2 courses and one additional from the list below) | ||
| IE 434 | Deep Learning: Mathematics and Applications |
4
|
| IE 522 | Statistical Methods in Finance |
4
|
| IE 525 | Stochastic Calculus & Numerical Models in Finance |
4
|
| IE 529 | Stats of Big Data and Clustering |
4
|
| IE 531 | Algorithms for Data Analytics |
4
|
| IE 532 |
Analysis of Network Data |
4
|
| IE 533 | Big Graphs and Social Networks |
4
|
| IE 534 | Deep Learning |
4
|
|
These courses can be taken as MSFE electives and will enhance the Advanced Analytics in Industrial & System Eng Concentration |
||
| IE 400 | Design & Analysis of Experiments |
4
|
|
IE 410
|
Advanced Topics in Stochastic Processes & Applications
|
4
|
|
IE 411
|
Optimization of Large Systems
|
4
|
|
IE 510
|
Applied Nonlinear Programming
|
4
|
|
IE 511
|
Integer Programming
|
4
|
|
IE 514
|
Optimization Methods for Large-Scale, Network-Based Systems
|
4
|
|
IE 521
|
Convex Optimization
|
4
|
|
IE 523
|
Financial Computing
|
4
|
|
SE 524
|
Data-Based Systems Modeling
|
4
|
|
Hours needed to satisfy the concentration:
|
12
|
|
|
Automated Trading Practices (ATP)
|
||
|
Course
|
Course Title
|
Credit Hours
|
|
Required:
|
||
|
IE 421
|
High Frequency Trading Technology
|
4
|
|
Algo Trading Courses: pick one or two |
||
|
FIN 554
|
Algorithmic Trading Systems Design & Testing
|
4
|
|
FIN 556
|
Algorithmic Market Microstructure
|
4
|
|
Stochastic & Learning Foundations Courses: If you have picked one Algo Trading Course above only, then pick one of the following |
||
|
IE 410
|
Advanced Topics in Stochastic Processes & Applications
|
4
|
|
IE 434
|
Deep Learning: Mathematics and Applications
|
4
|
|
IE 518
|
Queueing Systems
|
4
|
|
IE 531
|
Algorithms for Data Analytics
|
4
|
| IE 534 |
Deep Learning
|
4
|
|
Hours needed to satisfy the concentration:
|
12
|
|
|
Computational Science and Engineering Concentration (CSE)
|
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For more information: https://cse.illinois.edu/cse-educational-programs/graduate-concentration/ Contact: Bryan Wang at bpcwang@illinois.edu **Please note: courses applicable to this concentration are approved electives for the MSFE Program. |