Michigan State University Data Science Capstone.
The data science capstone course is intended to provide students with an opportunity to put together what they have learned across multiple courses to develop a final project that demonstrates their ability to work in a team on real-world problems.
The capstone course has three major goals:
The class will meet three times a week during the 15-week semester and will be delivered synchronously. Students are expected to attend class during the designated class period (MWF 3:00-4:20pm). Classroom time will be divided across three broad activity categories:
Early in the semester, students will be divided into capstone teams of 4-5 people and assigned a semester long project with multiple milestones. The majority of a students grade will come from working constructively as a team to accomplish the project goals (as defined by the instructor and the project community partners). When possible, the majority of out-of-class time will be dedicated to tasks and deliverable that relate directly to the capstone team’s projects. Students should expect to spend an average of 10-15 hours a week outside of class working on their capstone projects.
Class sessions will be held three times a week and broken up into presentations, discussions, group work and programming activities.
Active class participation (led both by the instructors and by students) is critical to the success of this course. As such, you are expected to attend every class session, bring the required materials and actively participate in the in-class discussions and activities.
Students that have a justifiable need to miss class must notify via email, the instructor, the graduate teaching assistant and their project team prior to the start of class (exception to this rule is only provided for extreme cases).
There is a LOT of material to cover this semester. To help provide some structure the course will try to following a typical schedule.
Although teams are encouraged to complete things early, project milestones will typically be due every Sunday at midnight. In-class activities on most Mondays will involve reviewing project milestones, providing peer feedback and in-class time to prepare for next milestones. Details about the Milestones can be found on the course Schedule Page.
Starting with the second week, all project milestones will be turned in using the team’s Microsoft Team Channel or the team’s github repository stored on the MSU Gitlab page (Some projects may use github but should check project agreements and get permission from the instructor). All files in git should use “git friendly formats” (aka ASCII) such as Jupyter notebooks, html and Markdown. Instructors will automatically download changes to the repositories after the due date and check for contributions by all of the students. Feedback will be provided using “git issues” or via a pull/merge request. Students are responsible for knowing how to properly use “Git” and everyone on the team is expected to make and commit changes to the repository.
DO NOT WAIT until the weekend before something is due. Instructors have posted all team deadlines on the website specifically so teams can get a head start and turn things in early. You should make a plan with your team and stick to it. The instructor will give you plenty of information and notice so you can work ahead. NO extensions will be given and you will still need to make up all of the work.
Teams are expected to conduct multiple formal team meetings each week to work on the projects. Although some time will be provided during class to conduct meetings, students must work together to arrange regular meetings outside of class. Meeting agendas and notes are required for all meetings and should include the following:
Meeting notes are to be stored in the Microsoft Teams folder, should be kept up to date, clearly organized and easily accessible by the instructors so that they may check in at any time to evaluate progress and provide feedback for the team.
Student grades will be partially determine by how well you work as a team. Teamwork can sometimes be difficult but it is required when joining our modern workforce. Peer evaluations will be used to help the instructor evaluate team dynamics and provide support to the groups if there are some team dynamic issues that need to be resolved.
NOTE: Team peer evaluation surveys will be conducted using CATME, an on-line tool though the course Desire2Learn website.
It is expected that each team will email a weekly Three-by-three (3x3) reflection to the instructors every Monday (cc all team members). The 3x3 reflection will consist of three major topics with exactly three bullet points in each topic (not 2 or 4). The three topics include; 1) What your team accomplish since your last report, 2) Challenges, Questions or problems your team is trying to solve 3) Your teams plans for next week. Each of the 9 bullets in the 3x3 reflection should be no longer than a couple of sentences. Additional details can be placed in the same email after the report (not required).
A template for 3x3 email can be found here
Students will learn professional skills training in communication, teamwork and leadership. Curriculum for these training are provided by the NSF funded CyberAmbassador program and supported in part by Tau Beta Pi (the national engineering honor society). During these activities students will learn topics such as conflict management, solving problems in teams, conducting an effective meeting, diversity equity and inclusion, data ethics, etc. This curriculum is intended to be highly interactive and, whenever possible, relate directly to capstone project activities.
Completion of the entire CyberAmbassador curriculum will result in the students earning a Professional Skills Certificate.
Students who participate in all 9 of the CyberAmbassadors modules will earn the certificate of completion for that program. Earning this certificate is not a requirement to pass this class.
If a student misses one or more of the modules due to an excused absence, they still can choose to earn the certificate by attending the missing module through the CyberAmbassador program. Information about times for upcoming virtual workshops can be found here:
On Fridays teams will work together to review, practice and build tutorials for common tools used in DataScience. These projects are specifically selected to help student focus and practice their technical skills working as a team. The content of the projects will be constructed in to mimic the expectations of the capstone projects and will be designed to practice specific skills needed to complete the projects.
It is expected that students will be able to complete the majority of work for these projects during class. However, motivated teams are welcome to work on the projects outside of class as long as any students include everyone in their team in the problem solving process.
The class has some limited funds that can be used to purchase software licenses and other supplies in support of projects. The instructor has some flexibility on to what and how these items can be purchased.
To request funding please send a professional email to the instructors using the following guidelines:
Although it is better to overestimate rather than underestimate, overly large budgets may get rejected.
It is expected that the teams will talk to the instructors before sending in a request.
This course offers an honor’s option. Student’s taking the honor’s option will join the DTTD Management team. Members of the DTTD Management team will be added to a special Microsoft Team Channel and will be expected to coordinate with each other (and the instructors) to divide the required work needed to manage the DTTD git repository. This includes organizing the issues list, reviewing pull requests, adding new features to the repository and helping other members of the course with git related questions. This role doesn’t require that you are currently a git expert however in your duties on the management team you will be learning a lot about git.
To get credit for the Honor’s Option students must contribute to the DTTD management team and email a short (less than 1-page) report to the instructors before the last day of class with a short paragraph about what they learned being on the management team and a list of tasks/responsibilities that they were responsible for managing.
If you are interested in getting credit for the Honor’s option, please email to your instructors saying you would like to be included in the DTTD management team.
There are a variety of course activities, with percentages of total grade listed. More detailed descriptions of each activity can be found elsewhere in the syllabus.
Activity | Grade Percentage |
---|---|
In-Class Participation | 10 |
Team Logistics | 10 |
DataTools Tutorial Development | 15 |
Project Milestones | 20 |
Individual teamwork score | 20 |
Final Project Deliverables | 25 |
Total | 100% |
The following is an estimated scale used for grading. There are multiple opportunities for students to receive grade-related input from other students; notably regarding group participation and/or presentations. This data is only advisory to the instructions, who still maintains full responsibility for assigning the grade.
Scale |
---|
4.0 > 90% |
3.5 > 85% |
3.0 > 80% |
2.5 > 75% |
2.0 > 70% |
1.5 > 65% |
0.0 < 60% |
Information for this course is being managed via the course website:
Accompanying course information, including the official course calendar, can be found at this website. The course also may use a Desire2Learn page for assignment grading and organization, which can be found at http://d2l.msu.edu
Classes will meet weekly on Monday, Wednesday and Friday 3:00-4:20pm in Union 55.
If, during the semester there is a need, we have set aside the following zoom room for this course. Teams must notify the instructor before class if one of their members needs to connect to class remotely (ex. due to illness or travel).
Specific assignments and due dates will be maintained on the course schedule, which is linked to off the course website.
The “in-class” programming assignments are a critical part of the learning process in this course. To that end, you will need to ensure that you have the following:
All required readings will be provided as Open Educational Resource (OER) via link on the course website.
Instructor:
Dr. Dirk Colbry (he/him/his)
Institute for Cyber Enabled Research (ICER) and Department of Computational Mathematics, Science and Engineering (CMSE)
Email: colbrydi@msu.edu
Web: http://www.dirk.colbry.com
Office: EB 1516
Virtual Office: Dirk’s Zoom Office
Office Hours: Mondays 1:00-3:00pm Outside the Classroom (Union 55)
Graduate Teaching Assistant:
Henry Fessler
Department of Computational Mathematics, Science and Engineering (CMSE)
Email: fesslerl@msu.edu
Virtual Office: Henry’s Zoom Office
Office Hours: Tuesdays 9:00-10:00am, Thursdays 10:00-11:00am on Zoom. Alternate times and in person options on request.
Many of the project community partners will require students to sign an Non-Disclosure Agreement (NDA) and in some rare cases will be asked to sign an Intellectual Property (IP) agreement. Your instructor will work with you so that you understand your rights and you will not be required to sign either document. If students are unwilling or unable to sign these document they will be assigned to an alternative project.
Note: The above are examples of the standard agreements. Slight variations may be made depending on the project community partner’s needs and will be given to students to review before project selection.
This class is heavily based on material presented and worked on during class, and it is critical that you attend and participate fully every week! Therefore, class attendance is required.
Arriving late or leaving early without prior arrangement with the instructor of your session may be counted as an unexcused absence. Note that if you have a legitimate reason to miss class (such as job, graduate school, or medical school interviews) you must arrange this ahead of time to be excused from class. Three or more unexcused absences will result in the reduction of your grade by one step (e.g., from 4.0 to 3.5), with additional absences reducing your grade further at the discretion of the course instructor. If you are unable to attend class or complete assignments due to illness or self-isolation (as per the CDC recommended guidelines), your instructor will work to provide the necessary accommodations to ensure that your performance in class is not significantly impacted.
Follow the directions on the assignment submissions. Please do not make your instructors guess where things are. If it takes work to track something down then points will be taken off projects. If it is obvious to you then it may not be obvious to the instructors. Remember professionalism is a key learning goal in this course.
At times, we will send out important course information via email. This email is sent to your MSU email address (the one that ends in “@msu.edu”). You are responsible for all information sent to your university email and for checking this account daily.
Respectful and responsible behavior is expected at all times, which includes not interrupting other students, refraining from non-course-related use of electronic devices or additional software during class sessions, and not using offensive or demeaning language in our discussions. Flagrant or repeated violations of this expectation may result in ejection from the classroom, grade-related penalties, and/or involvement of the university Ombudsperson. In particular, behaviors that could be considered discriminatory or harassing, or unwanted sexual attention, will not be tolerated and will be immediately reported to the appropriate MSU office (which may include the MSU Police Department).
In addition, MSU welcomes a full spectrum of experiences, viewpoints, and intellectual approaches because they enrich the conversation, even as they challenge us to think differently and grow. However, we believe that expressions and actions that demean individuals or groups comprise the environment for intellectual growth and undermine the social fabric on which the community is based. These demeaning behaviors are not welcome in this classroom.
Michigan State University is committed to providing equal opportunity for participation in all programs, services and activities. Requests for accommodations by persons with disabilities may be made by contacting the Resource Center for Persons with Disabilities at 517-884-RCPD or on the web at http://rcpd.msu.edu. Once your eligibility for an accommodation has been determined, you will be issued a Accommodation Letter (formally known as a Verified Individual Services Accommodation or “VISA” form). Please present this letter to the instructor at the start of the term and/or two weeks prior to the accommodation date (test, project, etc.). Requests received after this date may not be honored.
Intellectual integrity is the foundation of the scientific enterprise. In all instances, you must do your own work and give proper credit to all sources that you use in your papers and oral presentations – any instance of submitting another person’s work, ideas, or wording as your own counts as plagiarism. This includes failing to cite any direct quotations in your essays, research paper, class debate, or written presentation. The MSU College of Engineering adheres to the policies of academic honesty as specified in the General Student Regulations 1.0, Protection of Scholarship and Grades, and in the all-University statement on Integrity of Scholarship and Grades, which are included in Spartan Life: Student Handbook and Resource Guide. Students who plagiarize will receive a 0.0 in the course. In addition, University policy requires that any cheating offense, regardless of the magnitude of the infraction or punishment decided upon by the professor, be reported immediately to the dean of the student’s college. (See also the Academic Integrity webpage.)
It is important to note that plagiarism in the context of this course includes, but is not limited to, directly copying another student’s solutions to assignments; copying materials from online sources, textbooks, or other reference materials without citing those references in your source code or documentation, or having somebody else do your in-class work or homework on your behalf. Any work that is done in collaboration with other students should state this explicitly, and have their names as well as yours listed clearly.
More broadly, we ask that students adhere to the Spartan Code of Honor academic pledge, as written by the Associated Students of Michigan State University (ASMSU):
“As a Spartan, I will strive to uphold values of the highest ethical standard. I will practice honesty in my work, foster honesty in my peers, and take pride in knowing that honor is worth more than grades. I will carry these values beyond my time as a student at Michigan State University, continuing the endeavor to build personal integrity in all that I do.”
Personal assignments and peer review information materials submitted for this class are generally considered confidential pursuant to the University’s student record policies.
However, for many assignments this course is partnering with partners outside of MSU and students should be aware that instructors will not be able to maintain confidentiality with respect to project deliverables and anything that may come up which conflicts with their responsibility to report certain issues to protect the health and safety of MSU community members and others.
As the instructors, we must report the following information to other University offices (including the Department of Police and Public Safety) if you share it with us: suspected child abuse/neglect, even if this maltreatment happened when you were a child, allegations of sexual assault or sexual harassment when they involve MSU students, faculty, or staff, and credible threats of harm to oneself or to others. These reports may trigger contact from a campus official who will want to talk with you about the incident that you have shared. In almost all cases, it will be your decision whether you wish to speak with that individual. If you would like to talk about these events in a more confidential setting you are encouraged to make an appointment with the MSU Counseling Center.
The syllabus may also be adjusted if needed. These types of changes will be announced during class, by email and/or in the course website.
All lectures, videos and notes provided in this course are copyrighted by the university. Recording of lectures and/or commercialization of other university-provided course materials is not permitted in this course.
Article 2.III.B.4 of the Student Rights and Responsibilities (SRR) for students at Michigan State University states:
“The student’s behavior in the classroom shall be conducive to the teaching and learning process for all concerned.” Article 2.III.B.10 of the SRR states that “The student and the faculty share the responsibility for maintaining professional relationships based on mutual trust and civility.”
General Student Regulation 5.02 states:
“No student shall . . . interfere with the functions and services of the University (for example, but not limited to, classes . . .) such that the function or service is obstructed or disrupted. Students whose conduct adversely affects the learning environment in this classroom may be subject to disciplinary action through the Student Judicial Affairs office.”
Michigan State University is committed to ensuring that the bereavement process of a student who loses a family member during a semester does not put the student at an academic disadvantage in their classes. If you require a grief absence, you should complete the “Grief Absence Request” web form no later than one week after knowledge of the circumstance. I will work with you to make appropriate accommodations so that you are not penalized due to a verified grief absence.
If a student is exposed to someone who is ill, they will stay home, contact a health care provider and follow all public health recommendations. There are multiple policies available to complete course work. Please talk to your instructors and review the university policies.
In the event that the instructor gets ill, the course will continue. Backup instructors have been identified and will step in.
Written by Dr. Dirk Colbry, Michigan State University
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.