DATA-DRIVEN DECISION ANALYTICS FAQS
The degree requires 25 semester units: 12 technical units, 5 capstone project units, and 8 units in Engineering Leadership.
Evening schedule for Fall 2016:
- IEOR 241 Risk Modeling, Simulation, and Data Analysis, 6-9pm Monday evenings
- IEOR 240 Optimization Analytics, 6-9pm Wednesday evenings
The Spring 2017 schedule is under construction. The Spring 2016 schedule is currently:
- IEOR 290, Fundamentals of Machine Learning & Data Analytics, 6-9pm Tuesday evenings
- IEOR 242, Applications in Data Analytics, 6-9pm Wednesday evenings
Master of Engineering curriculum covers a breadth of business and leadership topics through 6 units of coursework offered in compliment to the technical courses and capstone projects. Pre-semester intensive “boot camp” classes offer a intensive interactive, participation-based experience. Students analyze real business situations through case studies dealing with topics such as negotiations, organizational behavior, R&D technology management, and ethics. In the second semester, explore fundamental operational, leadership, and financial concepts relevant to technology-driven enterprises by studying such topics as accounting and finance, product management, and entrepreneurship. Topics are subject to change as we innovate our curriculum.
Upon completion of program requirements, students receive the Master of Engineering (MEng) degree in Industrial Engineering & Operations Research with an emphasis in Data-driven Decision Analytics.
Degree completion is expected within 2 academic years (fall/spring semesters x 2) from enrollment, and maximum 3 years (fall/spring semesters x 3) with approval. Applications are currently accepted starting the fall semester only. We currently do not offer summer courses for this concentration.
We seek candidates with strong quantitative foundations and demonstrated leadership potential. The program welcomes recent college graduates as well as early-to-mid career professionals. Some of the majors that prepare students for the Decision Analytics concentration include Statistics, Math, Computer Science, Physics, Economics, Systems Engineering, and Industrial Engineering.
- Class Profile 2015-16
- Cohort size: 12
- Ages: 23-48 Median: 25 Mean: 28
- 50% women
- Average work experience: 3.5 years
- Current Employers: Chevron, Electronic Arts, Ernst & Young, Facebook, Google, Mercedes, MIMOSA Networks, Mochi Group, OSIsoft, Prysm, Sungevity, Stanford
- Undergraduate Schools: UC Berkeley, PSG College of Technology (India), Stanford, Tech University Darmstadt (Germany), San Jose State, UC San Diego
GRE scores are not required for the Data-driven Decision Analytics concentration but are strongly encouraged; GMAT scores are also accepted. If you do not provide test scores, please highlight your relevant coursework, grades, and work experience in your statement of purpose, in addition to submitting transcripts and a resume.
Fall 2015 Class Profile:
Median age: 25, Average age 28
Average work experience: 3.5 years
- Electronic Arts
- Ernst & Young
- MIMOSA Networks
- Mochi Group
- Stanford University
We are not longer accepting applications for this program for future enrollment.
The current rate of admission is 30%.