This syllabus is subject to change based on specific class needs, especially the schedule. Significant deviations will be discussed in class. Individual exceptions to the policies and schedule are granted only in cases of true emergency. Please make arrangements with me if an emergency arises.
Note: This is a compressed version of DATA 401 designed to be run in a half-semester.
The senior project is the culminating experience of a student’s major in Computer Science and draws upon everything the student has learned over the course of their studies. The project itself is a means to an end and not the ultimate goal of the capstone experience. Sufficiently interesting and complex projects rely on an abundance of existing research and fundamental principles of computing. The project is, from this perspective, a concrete instantiation of these ideas and principles. By carrying out the project and presenting their work to technical and non-technical audiences students can demonstrate their understanding and mastery of some core element of the computing sciences as it appears in the real world context of their project.
Students are ultimately working towards pinpointing general, abstract, or theoretical concepts that support their project and clearly articulating how their work is a specific instance of these concepts. An important part of this process is the identification of seminal scholarly work that addresses the concept and its applications. Students too often attempt to reinvent the wheel in the course of their capstone work. Occasionally they’re unaware that the wheel already exists. The emphasis on fundamentals is about identifying the wheels, the documents that lay out the general principles of those wheels, and focusing on applying those principles to the specific needs of the project. In doing so the student will better understand where their work sits in the broad spectrum of computing and can present it as such.
DATA 401 is focused on developing a detailed proposal for the senior project wherein the project’s place in data science and the domain from which their problem is drawn is clear and a workable plan for completing the project in DATA 402 is established. Students will take the half-semester to research topics surrounding their project, identify the wider context in which their work fits, and prepare themselves to immediately begin implementing their proposal the in DATA 402. Throughout the semester, students will make regular checkpoint presentations demonstrating their progress. At the end of the semester, students well present their proposed project to a general audience.
Students in this course are expected to be respectful of their peers and the instructor. As this course is comprised entirely of student presentations, it is crucial that all students are always present and always on time. Failure to arrive on time and be a productive member of the course will have a detrimental effect on the final grade and leaves a bad impression with faculty that are likely targets for job and graduate school recommendations.
The following elements of DATA 401 contribute to the overall capstone grade:
Students can expect to give a 5 to 7 minutes checkpoint presentation on a nearly weekly basis. Checkpoints for DATA 401 correspond to sections of the written proposal and students can expect to have at least one checkpoint per section. Refer to the proposal documents for more details about each checkpoint topic.
At each checkpoint presentation, students are expected to demonstrate progress towards understanding the week’s topic as it relates to your project. These presentations are meant to be an opportunity to get feedback from peers and the instructors. A students understanding of the topic need not be complete and they are expected to evolve as the semester progresses.
Halfway through the course students will give a 10 to 20 minute technical presentation. The goal of this presentation is to present the technical details of the concrete instantiation of a foundational piece of data science in the context of the capstone project. Students can consider issues with acessing and preparing data, analysis, modeling, visualization, etc. The key factor is that the subject matter is a relevant foundational principle in data science and the means by which you present that topic are through the tools and techniques you need to use to complete your project in DATA 402.
The details of the proposal are given in a separate document.
Students will receive an IP for this course at the completion of the course. When DATA 402 is completed and the capstone experience is done, a final grade will be determined and applied to both DATA 401 and DATA 402. Students will receive regular feedback about their standing and are always welcome to discuss their current grades with one or both of the instructors. Grades will be determined based on the following items:
More abstractly, what all of the above elements reflect is a student’s:
The following examples provide an idea of what we are looking for in the above items. These are rough guidelines only! Assessment can vary considerably depending on the project.
The weekly workload for this course will vary by student but on average should be about 6–8 hours per week. Since class meetings are only scheduled for 1 hour a week, we expect students to dedicate at least 5–7 hours a week towards the development of their project proposal and implementation. This time can include research, coding, writing, meeting with professors, and so forth. Being a capstone project, it is likely that your weekly work will occasionally exceed the expected amount – everything takes longer than you think!
Checkpoint presentations will occur on roughly a weekly basis. Unless otherwise specified, the topics listed below are the topics of checkpoint presentations. These topics correspond to some or all of sections of the final proposal. This calendar is subject to change based on the circumstances of the course.
Because this course is being compressed and combined with DATA 402 in a single semester, both schedules are given below.
| Week | Date | Checkpoint |
|---|---|---|
| 1 | 01/25 – 01/29 | Initial Meeting |
| 2 | 02/01 – 02/05 | Project Ideas/Background |
| 3 | 02/08 – 02/12 | Foundations/Tech talk proposal |
| 4 | 02/15 – 02/19 | Tech Talk |
| 5 | 02/22 – 02/26 | Features & Specifications, Plan & Timeline |
| 6 | 03/01 – 03/05 | Proposal checkpoint. |
| 7 | 03/08 – 03/12 | Proposal Due. Proposal Presentation. |
| 8 | 03/15 – 03/19 | (No checkpoint) |
| 9 | 03/22 – 03/26 | Implementation checkpoint 1. |
| 10 | 03/29 – 03/31 | Implementation checkpoint 2. |
| 11 | 04/05 – 04/09 | Implementation checkpoint 3. Poster draft. |
| 12 | 04/12 – 04/16 | Implementation checkpoint 4. Poster draft. |
| 13 | 04/19 – 04/23 | Implementation checkpoint 5. Poster draft. |
| 14 | 04/26 – 04/30 | Scholar’s Day? Poster due. |
| 15 | 05/03 – 05/05 | Implementation checkpoint 6. Bibliography due. |
| 16 | 05/08 | Final presentations. |