Course Syllabus

MTH540, MTH440, and EAS621

Mathematical and Computational Consulting

Professional Preparation Program

Fall 2017, 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. Please check mycourses for course updates.

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: 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.