Course Syllabus
MTH540, MTH440, and EAS621
Mathematical and Computational Consulting
Professional Preparation Program
Fall 2019, UMass Dartmouth
This course will satisfy University Study 5-B (Learning through Engagement)
Place and Time
The class meets once a week on Wednesday: 3:00 - 5:30 PM in room: LARTS218.
Office Hours
Office hours schedule can be seen from the following link.
Attendance & Focus of Attention
The course will give students an experience much more like the
technical workplace than the experience in most courses.
We only meet once a week and you are expected to come to class on-time. Therefore, attendance is mandatory,
as is being on-task and participating in class activities.
By taking this course, you can think of like you work for a company. Deadlines are strict and slacking off
is not an option.
Two (2) missed classes without explanation may result in a grade of F without further discussion.
Course Overview
The course will focus on learning, analyzing, and attempting to solve challenging
real world research problems. The problems are selected from multidisciplinary projects solicited
from various research groups at UMass Dartmouth, from local and national industries/universities/
labs, and from crowdsourcing websites. Developing skills to utilize computer algebra systems and
problem solving environment software to rapidly prototype, quantify, visualize, and help understand
or gain insights into the problems are the main objectives of this course.
Course-Specific Learning Outcomes
Students will experience hands-on training to analyze, study,
and solve challenging research problems, where solutions are not fully understood or not yet
available. Faculty instructors/advisors will help students in developing skills to think out of the box,
to search relevant literature, to articulate ideas and discoveries through presentations and technical
writing, and to build strong working relationships with their peers with different level of expertise
as teams. Learning to honestly disseminate results to promote reproducible research is an expected
outcome of this course.
University Studies Learning Outcomes
Students will experience discovery-based learning though
engagement in research activities for solving real world problems. They apply techniques and
methods learned from previous math, science, and engineering courses and the relations between
them to help understand these problems and to propose new approaches. Through multidisciplinary
collaborations among peers from different majors, and intensive communication with the industry,
lab, or university clients that presented the problems, students shall develop skills in translating and
communicating ideas and gain a unique understanding of how to work with people from different
backgrounds and levels of expertise.
Mathematics Department Secretary
Jill Peters, the Math Department's secretary serves as the point of contact person with industry leaders, and matching students with internships.
She will act as a project manager to ensure all dates, requirements, and deadlines are met, as well as handle all administrative tasks
associated with this program.
Grades
We have responsibilities to deliver products (final report, research codes, etc) to our clients. Hence, your grades
will be consulted with our clients too. Your grades will be based on the following distribution:
- Final Report or Final Product (including Codes): 55%
- Bi-Weekly Progress Report Presentation: 15% (Recorded)
- Weekly Updated Research Diary: 15%
- Final Presentation: 15%
Keep in mind that attendance and class participations are mandatory.
Grade Change Policy
From memorandum on course procedures: "No final grade may be changed as a result of re-examination,
the re-evaluation of work submitted, and/or assigning additional [extra credit] work before or after
the end of the term, unless all students enrolled in the class are afforded the same opportunity".
Academic Dishonesty
Please consult UMass Dartmouth Student Academic Integrity Policy.
Tips
If the mathematical models or the problems are too hard, you may solve simpler models numerically to plot
solutions in order to gain more insight. Since this is not a numerical analysis class, utilizing ready to use software, specialized package, and free toolboxes
to help your numerical experiments are recommended. In short, your final report is like your neat research diary organized in the style of
research paper that contains your numerical experiments, mathematical derivations, advises from your classmates, and discussions to make things clear for you.
Having a private research diary in sharelatex and in a git repository such as bitbucket that can be shared with other students and instructors is recommended. The git repository
can also be used to upload your research codes to promote reproducible research, which can later be included in your linkedin CV.