Students will;
- Integrate previously learned material in a novel application area of data science.
- Complete a significant project using data science methods and principles.
- Present results of your project in a professional forum or to a business client.
- Document your data science journey and skills through a blog.
- Leverage modern data science tools to share your work (e.g. GitHub)
You will need to get your data science faculty advisor to give you permission to add the course. Your senior project is an opportunity for you to build a portfolio of work that documents your skill sets as an undergraduate data scientist. Here is an example from Andrew Wolfe. Each project will also need to include a few publishable articles that will be shared on our LinkedIn Data science group.
The type of data or coding that you tackle does not have to be like Andrew's project. Some students have built R packages for clients as an example of something different. However, we do want your senior project to start a project from raw data and grow to a final analysis or other data science deliverable. Each student will also be required to present at a conference or to a client. Often, the Research and Creative Works Conference at BYU-I is used.
Your senior project is built to give you a space to develop your own final product as a data science major. It is important to think about when and how this class is taken during your major.
We recommend that you take it your last semester and expect that you will take it during your senior year. This is a capstone experience for you to demonstrate to yourself and employers that you can use the tools you have learned throughout the data science program to complete original self-directed work.
You will be responsible to submit a project proposal before the semester in which your senior project credits begins. This proposal will be a one-page document that proposes a novel question or problem that you would like to address. The proposal should include information about the type of data you will need to find and a list of professors that you would prefer to be your mentor on the project.
This senior project is self-directed. Your faculty mentor will work with you to have 1/2-hour scheduled for supporting your project. You will be responsible to complete 126 hours of work on your project to be able to earn an A grade. Your hours together with your deliverables documented below will define your final grade in your senior project. You will use the course provided time management tool to track and report your hours weekly.
Each project will have its own unique deliverables that will be negotiated in the project proposal listed below. For example, some projects could require the development of an R package, a presentation to a client, or deeper understanding of machine learning techniques. All projects are expected to have the following deliverables delivered during the semester at the specified week in the semester.
| Item | Description | Date |
|---|---|---|
| 1 | Draft project proposal submitted | Before the semester starts |
| 2 | Finalize project proposal & Draft blog created | Week 1 |
| 3 | Finalized data science resume submitted | Week 2 |
| 4 | Data ingested or documented process for ingestion & First post about your project | Week 4 |
| 5 | Update project proposal with detailed steps to completion & Second post about your project | Week 6 |
| 6 | Submit abstract to R&CW conference | Week 7 |
| 7 | Draft version of final project post & Third post about your project | Week 9 |
| 8 | Build out Github with project work | Week 10 |
| 9 | Post final version of project post | Week 11 |
| 10 | Present at R&CW conference | Week 12 |
| 11 | Finish all materials and review blog with instructor | Week 14 |