Syllabus

Overview
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.
In addition to the project, students will hear from experts on a variety of topics to prepare them for post-graduation: from public speaking, reading/writing research papers, diversity and inclusion, how to lead a team remotely, everything about start-ups, etc.
 
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.
Collaborations
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.

Meetings

Class time
Each class session will begin with a mini-lecture, led by an expert on a topic that is useful for your professional career but often overlooked in traditional curriculums. 
Partners
Each group will meet with their respective partner on a regular basis to provide updates. The exact frequency will be collectively decided upon by the partner, your group, and Chris; however, the partner should be aware of your work at least once every 2 weeks. 
 

Deliverables and Grades

 

Lightning Talks

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)

  1. Ignite Talk (8 pts)

  2. Statement of work (2 pts)

Phase 2 (16 pts)

  1. Milestone #1 Presentation (Midterm) (9 pts)

  2. Partner Report + technical write-up (3 pts)

  3. Self- and peer- evaluation (2 pts)

  4. Review another group's partner report (1 pt)

Phase 3 (20 pts)

  1. Milestone #2 Presentation (11 pts)  

  2. Partner Report + technical write-up (5 pts)

  3. Self- and peer- evaluation (2 pts)

  4. Review another group's partner report (1 pt)

  5. Code (runs as advertised) (1 pt)

Phase 4 (18 pts)

  1. Milestone #3 Presentation (11 pts)  

  2. Partner Report + technical write-up (5 pts)

  3. Review another group's partner report (1 pt)

  4. Code (runs as advertised) (1 pt)

Phase 5 (38 pts)

  1. Poster and video recording (7 pts)

  2. Final website/blog (10 pts)

  3. Final Presentation to class (15 pts)

  4. Self- and peer- evaluation (2 pts)

  5. Review another group's blog (1 pt)

  6. Code (runs, is organized and readable) (3 pts)

Extra Credit (3 pts per award)

  1. GSD Award (best design)

  2. Benjamin Franklin Award (most innovative)

  3. Winston Churchill Award (best oral presentation)

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!

IACSLogo_RGB_UseOnDarkBackground_transpa
33 Oxford Street, G-107
Cambridge, MA 02138
lray@seas.harvard.edu