Data Science Capstone
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Prerequisite: Permission of instructor.
Course Restrictions: Restricted to students in the Master of Science in Data Science program. Restricted to Graduate Students.
This capstone course provides the culminating experience for students in the Master's in Data Science program. Soft skills such as effective communication are indispensable, and therefore teamwork is strongly recommended over individual projects. Students will conceptualize, propose, and execute an end-to-end data science project using real-world big data. The project will integrate skills and concepts learned throughout the program, including statistical analysis, machine learning, and communication of results. Under instructor’s guidance, students will identify a problem amenable to data science techniques, acquire appropriate datasets, perform exploratory data analysis, implement data cleaning, and feature engineering pipelines, train machine learning models, and measure model performance. The final project must be approved by a committee consisting of at least two of the MSDS faculty. Students are encouraged to submit the product to a data science conference or a peer-reviewed journal.
Credit: 3
Free Form Requirements
Prerequisites: Completion of at least 8 core courses in the Master's program in Data Science and Machine Learning. Students are allowed to work on the capstone project and enroll the last course of the program concurrently.