Concentration Selection/Self-Evaluation Form for The Master of Science Degree in Data Analytics Engineering

Transcription

1 Volgenau School of Engineering Office of Graduate Admissions & Enrollment Services MS 3D5, 4400 University Drive, Fairfax, Virginia Phone: ; Fax: ; Concentration Selection/Self-Evaluation Form for The Master of Science Degree in Data Analytics Engineering Please fill out this self-evaluation form to help us determine your best plan of study. Please make the best match you can between graduate and undergraduate s you have already, and the equivalent GMU s. When you are admitted to the MS in Data Analytics Engineering degree program, you will be advised as to what foundation s, any, you may be required to take. NAME DATE PREVIOUS DEGREE(S) G# Concentrations: Select ONLY One Concentration Applied Analytics Bioengineering Data Mining Digital Forensics Predictive Analytics Statistics for Analytics Individual Plan of Study If you have selected the Applied Analytics concentration then no further information is required. If you have selected Individual Plan of Study then specy a tentative plan of study using the table at the end of this form. For all other concentrations, fill in the corresponding table to determine you have satisfied the necessary prerequisites. Applied Analytics - For those selecting this concentration indicate in the table below how these prerequisites are met by matching these GMU equivalents to s from your previous

2 Calculus w/ Business Applications Math 108 Course #: Statistics I STAT 250 Course #: IT 106 Course #: Data Mining For those selecting this concentration indicate in the table below how these prerequisites are met by matching these GMU equivalents to s from your previous Data Structures CS 310 Course #: Formal Methods & Models CS 330 Course #: Systems Architecture CS 367 Course #: Assembly CS 465 Course #: Discrete Mathematics Math 125 Course #:

3 Digital Forensics - For those selecting this concentration indicate in the table below how these prerequisites are me by matching these GMU equivalents to s from your previous Operating Systems IT 342 Course #: CS 112 Course #: TCP/IP IT 341 or TCOM 535 Course #: Routing IT 445 or TCOM 515 Course #: Predictive Analytics - For those selecting this concentration indicate in the table below how these prerequisites are met by matching these GMU equivalents to s from your previous Applied Probability/Statistics STAT 344 Course #: Language CS 222 Course #:

4 Statistics for Analytics For those selecting this concentration indicate in the table below how these prerequisites are met by matching these GMU equivalents to s from your previous Calculus III Math 213 Course #: Probability Math 351 Course #: Matrix Algebra Math 111 Course #: Bioengineering for Analytics For those selecting this concentration indicate in the table below how these prerequisites are met by matching these GMU equivalents to s from your previous Calculus III Math 213 Course #:

5 Elementary Dferential Equations Probability for Engineers Math 214 Course #: STAT 346 Course #: Signals and Systems BENG 320 Course #: Individual Plan of Study For students that wish to craft their own plan of study, choose five possible (non-core) graduate level elective s (500 level or higher) related to your MS in Data Analytics Engineering interests. Interdisciplinary s can be selected with the following prefixes: Applied Information Technology (AIT); Science (CS, INFS, ISA, and SWE); Forensics (CFRS); Statistical Science (STAT); Systems Engineering and Operations Research (SYST, OR); Bioengineering (BENG, ECE). Please do select s entitled Directed Readings or Special Topics. Electives Course Number Course Name Students will be required to meet individual prerequisites.