Data, Models and Optimization Graduate Program
- Graduate Certificate
Fee may apply
The Data, Models and Optimization Graduate Program focuses on recognizing and solving problems with information mathematics. You'll address core analytical and algorithmic issues using unifying principles that can be easily visualized and readily understood. With advancements in computing science and systematic optimization, this dynamic program will expose you to an amazing array of applications and tools used in communications, finances, and electrical engineering.
You Will Learn
- Applications that build on or use convex optimization
- Ideas of self-concordance and complexity analysis
- Methods for analyzing and solving large scale problems
- Prototypes to develop accurate models and efficient algorithms
- Techniques for exploiting structure to improve efficiency
- Theoretical advantages of real-time reactive or automatic control systems
Who Should Apply
Engineers, investors, mathematicians and researchers who use scientific computing or optimization in their work.
Earning the Certificate
- Earn a Stanford Graduate Certificate in Data, Models and Optimization
- Begin the program any academic quarter that an applicable course is offered, subject to prerequisites
- Take courses for graduate credit and a grade
- Receive a B (3.0) or better in each course
- Complete 2 required and 2 elective courses
- Foundational courses do not count towards the program
A conferred Bachelor’s degree with an undergraduate GPA of 3.0 or better.
To pursue a graduate program you need to apply.
Tuition is based on the number of units you take. See Graduate Course Tuition on our Tuition & Fees page for more information.
Time to Complete Certificate
1-2 years average
3 years maximum to complete
Submit an inquiry to receive more information.
Recommended Foundational Courses
Data Mining Elective Courses
Finance Applications Elective Courses
Optimization Elective Courses