The Capstone course is open to all Harvard students interested in working on a team to integrate the data science and computational science knowledge acquired in core courses to produce an end-to-end solution to a complex real-world problem. The projects are selected so that current statistical, machine learning, computational, and engineering methods can be used. Most projects have been designed to address important contemporary business and societal issues.
This course will give you the opportunity to:
1) work as part of a team
2) integrate knowledge acquired in other courses
3) apply skills and ideas in computational and data science
Upon completion of the Capstone Project Course, you will be better prepared to conduct research at a professional level.
A significant component of the course will be regular feedback and guidance from the teaching staff, including explicit measures of evaluation and feedback on all aspects of the project, beginning with data acquisition, through project design and implementation. Additional feedback includes self-assessment and peer evaluation. You will be asked to evaluate each team member’s contribution as well as your own contribution to the project.
Since many employers consider the ability to engage in productive teamwork a requirement for success, we expect you to actively develop your collaborative skills, such as group management, interpersonal communication and conflict resolution.
Townhalls (a.k.a class time)
There will be a weekly one and a half hours “Town Hall” meeting with the entire class throughout the semester. These meetings will be designated for the lighting talks, short tutorials or guest lectures on non-technical subjects such as communicating in the professional world. See schedule for details. Attendance is mandatory.
Weekly meetings with TF
Each group will meet with their assigned TF each week. This will happen during the town hall meeting or with Pavlos.
Bi-weekly meetings with Pavlos
Each group will have 45 minutes of bi-weekly update meetings with Pavlos. At the end of each Phase, there will be a 60-minute milestone meeting during which you are expected to present the progress of your work. You will be graded on this presentation. You will keep logs of your work and share them with the staff before each meeting. This will ensure that the meetings are productive.
Deliverables and Grades
During the Town Hall meetings, we will spend a brief amount of time on class announcements followed by Lightning Talks or Ignite Talks by some of the groups. You will give two Lighting Talks talks during the semester.
Phase 1 (10 pts)
Milestone #1 Presentation (8 pts)
Partner report (2 pts)
Phase 2 (25 pts)
Milestone #2 Presentation (Midterm) (20 pts)
Partner report (5 pts)
Phase 3 (25 pts)
Milestone #3 Presentation (18 pts)
Partner report (5pts)
Self and peer evaluation (2 pts)
Phase 4+5 (40 pts)
Poster at showcase (8 pts)
Final website (10 pts)
Final Presentation (20 pts)
Self and peer evaluation (2 pts)
Learning Opportunities for this course
Feedback from the Instructor and Teaching Fellows
The largest component of the course will be the substantial feedback and guidance from the instructor and teaching fellows (TFs), including explicit measures of evaluation, feedback on all aspects of the project and its implementation, as well as self-assessment and peer evaluation. This feedback process will begin with the data acquisition and data exploration phase and extend through the design and implementation phase of the project.
Feedback from the Project Partner Organizations
You will also meet with your project partner organizations a few times but these meetings are for consultation and feedback only. Some partners are more hands-on than others; you and them will have the opportunity to determine the level of partner involvement during the course. As described in the previous paragraph, goals and guidelines are set during meetings with the instructor and TFs and you will be graded by the same people.
Feedback from and Interaction with your teammates
We expect you to work with your team members to develop your collaborative skills such as group management and conflict resolution, and to sustain good interpersonal relations. You will be asked to evaluate each team member’s contribution as well as your own contribution to the project. Many employers consider the ability to engage in productive teamwork a requirement for success.
Learning Outcomes for this course
After you successfully complete this course you will be able to:
Collaborate with others
Acquire, organize and process data (data analysis)
Create and outline solutions using statistics, machine learning and mathematical modeling (data modeling)
Implement those solutions
Communicate and defend your work
Practice professional skills by communicating with partners from outside the University in a courteous and punctual manner.
Change the world!