Please share this online course information with any students who may be interested in joining. Also, please let me know if you also have content or a lecture topic that you'd like to share with the class. A substantial portion of the class is working
on innovative dynamic optimization projects so ideas for group projects are also welcome.
The Dynamic Optimization Course starts Tuesday, 10 January 2018 (14 weeks). A few new aspects of the course for this year are an increased focus on mathematical dynamic modeling, a new Python interface to APMonitor that will be introduced in the course,
and more hands-on activities with a MIMO Temperature Control Lab. The course is available for remote participants (WebEx) 3-4 PM Mountain time on Tuesdays and Thursdays. The course is freely available but limited to 200 remote participants. The lecture material
is pre-recorded and the WebEx sessions are designed for interactive and hands-on participation. To join the course, please fill out a course information form at
https://goo.gl/ZpU5fs and obtain (build or
buy) an Arduino temperature control lab.
