Capstone Project for Data Science Sponsor Document
Department: Mathematics and Statistics, College of Sciences and Mathematics

Sponsor Name: 
Course Instructor: Nedret Billor
A data science capstone project is a crucial part of the curriculum for graduate students studying data science. It allows students to apply the knowledge and skills they have gained through coursework to solve real-world problems and showcase their expertise, creativity, and problem-solving skills to potential employers. Through our Master's Data Science and Engineering-Data Science program, we are actively seeking corporate partners/research groups to collaborate with us in advancing data science through cutting-edge research, innovation, and entrepreneurship. We believe that partnering with companies/research groups can provide our students with access to industry/research data, exposure to industry/research practices and workflows, and networking opportunities while also allowing our partners to benefit from the practical experience of working with skilled and motivated data science students.
Desired components of Capstone Projects:
•	A well-defined problem: The project should have a clear and well-defined problem statement. The problem should be challenging, meaningful, and relevant to the industry or domain.
•	Real-world data: The project should involve working with real-world data, which is often messy and complex. This will provide students with a valuable learning experience and help them develop their data manipulation and analysis skills.
•	Application of data science techniques: The project should involve the application of various data science techniques, such as data cleaning, data exploration, feature engineering, modeling, and evaluation.
•	Collaboration and teamwork: Capstone projects should involve collaboration and teamwork. 
•	Creativity and innovation: Capstone projects should encourage students to think creatively and come up with innovative solutions to the problem. 
•	Project management: Capstone projects should involve project management skills, such as setting timelines, milestones, and deadlines. 
•	Presentation and communication skills: Capstone projects should culminate in a final presentation, where students present their findings and results to a diverse audience. 
Approval process and Timeline: The capstone projects officially start in the second week of 

August, which is the beginning of the Fall semester, and should be completed by the end of November, which is the end of the Fall semester. The project proposals are reviewed by the program faculty and corporate partners to ensure that they meet the program's standards and are aligned with the industry's needs. The faculty provide guidance and feedback throughout the project, and the students are expected to present their progress regularly. The final presentations are evaluated by the program faculty and corporate/research group partners, and the students receive feedback on their work.

Project Summary: 

Project Objectives: 

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Key questions to answer:

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Key Skills:

Examples:
•	 Python, 
•	machine learning, 
•	scikit-learn, 
•	tensorflow
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Key Deliverables:

Examples:
•	Script in Python that can be run on the dataset 
•	Written report summarizing all methods considered, along with advantages/disadvantages of each. For the method recommended and implemented by the team, the report should include a detailed description, justification for why it is the best one to use, and answers to the questions outlined above.
•	Presentation to Industry Partner’s Team of summary

More..

Operating rhythm: 

•	Minimum weekly touchpoints between Industry Partner Team (IPT) and AU DS  capstone team.  Students report on findings and progress, following IPT’s weekly standup format.
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Key contacts (Industry Partners Team):
Name:
Title: 
Mobile:  
e-mail: 
Role on the project :  IPT’s project leader and subject matter expert (SME) for students  to engage with weekly (biweekly?)

Second Person?
Title: 
Mobile:  
e-mail: 
Role on the project: IPT  project coordinator (periodic check-ins with Dr. Billor,   and IPT’s project leader, the student team to ensure that the collaboration is running smoothly)