Fall 2022 Syllabus - The Data Mine Corporate Partners

The Data Mine Team uses a shared email which functions as a ticketing system. Using a shared email helps the team manage the influx of questions, better distribute questions across the team, and send out faster responses. You can write to [email protected].

Use this table to send your questions to the most appropriate email. If you’re not sure who to ask, navigate to the Questions page for more details.

Your Corporate Partner Mentor(s) are employees of the company you are working with. You will meet once a week with them online (unless the company is in West Lafayette, IN or visiting Purdue for a meeting). Please treat all communication with them in a professional manner – they are like your supervisor during an internship. They also act as a product owner and can help to answer questions or find resources for any product specific questions that you have during the project.

Our Corporate Partner TAs will serve as peer mentors and team leaders for each of our projects. Nearly all of our CRP TAs have been in The Data Mine Corporate Partners program in past years and many are returning to the same project. The CRP TAs will lead the weekly student meeting (lab – 2 hours) when you are not meeting with the Corporate Partner Mentor(s). They should also be the first person to go to when you have a technical question or questions about your project.

The data scientists employed by The Data Mine are here to help students with the technical topics and concepts that they will encounter during their projects. The data scientist team has a varied background in topics such as natural language processing (NLP), geospatial information systems (GIS), high performance computing, and machine learning.

If you have a question for a member of the Data Science team, please email [email protected] and your question will be answered by a member of the Data Science Team. If our doors are open, you can drop by and ask for help. They will bring in other members of the team as needed. They are here to help so don’t be worried when asking questions!

When scheduling a meeting with a data scientist keep in mind that they are designed to be collaborative. The team wants to see any solutions that you’ve attempted and where you may be getting stuck. Also, for more complicated questions it helps to give some advance notice of the topics over email. We aren’t experts in all of data science and some research may be required.

The Data Mine staff offer office hours by request. Please email [email protected] if you need to request a meeting. Students are always welcome to stop by staff offices Monday - Friday in MRGN 132 - 148.

50-minute team meeting

This meeting will occur synchronously online via MS Teams unless your Corporate Partner Mentors are located in West Lafayette or visiting campus. Online links are shared via a calendar invite at the beginning of the year. You can join this meeting from anywhere, but please follow the “net-etiquette” guidelines to find a quiet space.

1 hour 50-minute student labs

This meeting will occur in person for all teams. This is dedicated work time with your team members to collaborate on your project and to work as a larger group or as sub-teams. The meetings will be held in Hillenbrand Residence Hall (HILL) at 1301 Third Street, West Lafayette, IN 47906 or the Burton D. Morgan Center for Entrepreneurship (MRGN) at 1201 W. State St., West Lafayette, IN 47907.

We do NOT accept late work, unless there are extenuating circumstances.

Extenuating circumstances do NOT include:

All students get one dropped sprint report. Using the drop early in the semester does not give you the excuse to ask for another drop or late work later in the semester.

It is better to submit a partially done report than nothing at all. Partial credit can be earned for work turned in on time. The electronic submission systems also do not allow for late work.

This is a research-type, project-based course, so the majority of your grade for the semester will be determined holistically based on work with Corporate Partners in addition to reports and other assignments per the schedule. Students will receive their own individual grade, but the success of the group will be a component of that individual grade.

It is very important to check the Brightspace, Gradescope, and The Examples Book pages frequently! Please review the schedule. More details for each assignment will be available in The Examples Book. Due dates are listed in the semester schedule

At the beginning of the semester, you will need to complete the following: syllabus quiz, agile training, and agile quiz. Details are posted on Sprint 1.

The Data Mine does not conduct or collect an assessment during the final exam period. Therefore, Corporate Partner Courses are not required to follow the Quiet Period in the Academic Calendar.

During the last week of fall semester in December, there will be a final presentation to showcase the work you have done throughout the semester and what you plan to accomplish in the spring semester. All Corporate Partner students will be required to make a final presentation with their teams and present it to their Corporate Partner leadership team. More details will be forthcoming and posted in The Examples Book.

The general guidelines The Data Mine uses for evaluating your work with Corporate Partners are the following:

The numbers in parenthesis next to the letter grades are the numerical values that will be entered in Brightspace for your Corporate Partners Mentor Evaluation grade.

This course will follow the 90-80-70-60 grading scale for A, B, C, D cut-offs. If you earn a 90.000 in the class, for example, that is a solid A. +/- grades will be given at the instructor’s discretion below these cut-offs. If you earn an 89.11 in the class, for example, this may be an A- or a B depending on the course grade distribution at the end of the semester.

This course permits you, the student to participate in a class project that has been sponsored by a third party other than the University. The University encourages and supports your participation in this practical learning experience. Although your course requirements may include a practical learning project, you are not required to participate in a project that is sponsored by an outside third party. Prior to your participation in a project sponsored by an outside third party, we would like you to carefully consider that your participation (i) may require you to assign your intellectual property (IP) rights to any intellectual property for which a student would retain ownership under the University’s Policy I.A.1 on Intellectual Property and/or (ii) may require you sign a non-disclosure (confidentiality) agreement with the sponsor. If you sign an agreement regarding intellectual property rights or a non-disclosure agreement, you may incur personal liability (with respect to breach of a non- disclosure agreement) or you may lose economic benefits associated with your ownership of intellectual property (with respect to a license or assignment of intellectual property). You are encouraged to retain independent legal counsel for advice on these types of agreements. In addition, if you choose not to sign a non-disclosure or intellectual property rights agreement, you may be reassigned to a different project or you may not be able to participate in The Data Mine Corporate Partners.

It is important to note that you are working on real-world problems that your Corporate Partner is trying to solve. These projects weren’t created as busywork to keep you occupied for 9 months; you have the opportunity to make a real impact with your Corporate Partner. Past work from Data Mine students has been put into production code!

With that being said, the work you do and the data you have access to must be kept fully confidential! Nearly all Corporate Partner students will be required to sign an NDA and/or IP agreement with the company. Even if you do not have to sign an NDA for your project, please keep the project details private. While each NDA will have unique terms, some basics include: