A major component of this class is the group project you will be working on from now until the end of the semester. Not only is this project a large fraction of your final grade, it also represents an opportunity to explore a topic from class in a more in-depth manner or to try something new and exciting in the realm of AI. The class project will consist of several milestones, including a project proposal (due on 10/12 at 11:59PM), interim project update (due on 11/12), a live demo (to be presented in class the week of 11/26), and a final deliverable including a full report and complete code and data (due 12/12).

For this assignment, your group should assemble a one-page project proposal that contains the following components:

Component 1: Introduce Your Group

At the top of your proposal document, list the individual members of your group (names and email addresses). For this project, groups should consist of three or four students. If you are having trouble assembling or finding a group, please let Prof. Scheirer know ASAP. All group members are expected to contribute equally to the project. A group member assessment form will be circulated near the end of the semester to help gauge this expectation.

Component 2: Choose Your Topic

Your proposal's title should reflect the chosen topic. You are free to choose any topic related to AI that interests your group. However, the chosen topic must be of sufficient scope and difficulty to provide enough work for your group from now until the end of the semester. You can also choose one of the following topics, which have already been pre-approved as being sufficiently rigorous:

Component 3: Describe the Elements of Your Project

The bulk of your proposal should describes the elements of your project in sufficient detail. First, outline the specific tasks you hope to accomplish. Assign estimates to how long you think those tasks will take to complete. What language will you use to write your software? List any development tools and software libraries you intend to use. For this project, you are encouraged to use existing open source libraries to support your project development where appropriate. If your project is data-driven (i.e., you plan to use machine learning), explain where your training, validation, and testing data is going to come from. Identify specific criteria for success (how will you know if your project outcomes are favorable?). Make sure you describe how the software will be used in practice (i.e., how do things look from the user's perspective?).

Submitting Your Proposal Document

Each group needs to submit one copy of their proposal (in PDF format) via email to Abby (agraese@nd.edu). Prof. Scheirer will grade these and provide guidance on the difficulty, scope and timing of the overall project. Feedback will be returned to you by the end of Fall Break.

If you have specific questions about this proposal before it is due, please reach out to Prof. Scheirer or Abby during office hours, or via slack. This proposal is worth 50 points.