Eligibility
| CU Affiliation | Eligibility |
|---|---|
| Alumni | |
| Emeritus | |
| Faculty & Staff | |
| Persons of Interest (POIs) | Types C, D |
| Retirees | |
| Students | |
| Campuses | Boulder |
Conditions
The software can be used for:
- Academic teaching & learning
- Academic research (nonprofit)*
The software can't be used for:
- Commercial purposes (for profit)
- Non-academic research
- Administrative purposes (university business)
Where it can be installed
- University-owned devices
- Personal devices
Other conditions
Non-CU affiliates may run MATLAB, MATLAB Parallel Server, and other programs on university-owned devices provided that the programs are for academic and non-commercial use only.
*Academic research is research that is conducted on campus and is in support of the university's degree-granting requirements or a faculty member's tenure.
Cost
Available at no cost to eligible affiliations.
How to get it
Download MATLAB using a MathWorks account from the CU Boulder - MathWorks Portal using the instructions and codes posted specifically for students or for faculty/staff.
Your MathWorks account can be used for downloading, updating, and licensing MATLAB and for accessing MATLAB Mobile (a free app) on an iPhone, iPad, or Android device.
MATLAB licenses expire in December. To renew a license, choose "Licensing" from MATLAB's Help menu and select "Update Current License." If not updated by the end of December, a user must reactivate the license by running the computer's Activate MATLAB utility or take the opportunity to upgrade to the latest version by downloading it from the personal MathWorks account.
Support
If you need assistance, contact MathWorks technical support or the IT Service Center at oithelp@colorado.edu or 303-735-4357.
Documentation
Your MATLAB access includes online, on-demand MATLAB courses. These interactive, self-paced classes provide progress reporting and certification of completion, and cover topics such as:
Core MATLAB
- MATLAB Fundamentals (20 hrs, 17 lessons)
- Data Processing and Visualization (7 hrs, 10 lessons)
- Programming Techniques (14 hrs, 9 lessons)
- Financial Applications (14 lessons)
Data Science
- Machine Learning (14 hrs, 7 lessons)
- Deep Learning (14 hrs, 12 lessons)
Computational Mathematics
- Solving Nonlinear Equations (1.5 hrs, 5 lessons)
- Solving Ordinary Differential Equations (2 hrs, 4 lessons)
- Introduction to Linear Algebra (1.5 hrs, 3 lessons)
- Introduction to Statistical Methods (2 hrs, 4 lessons)