This course provides a unique opportunity for students in the M.S. in Data Science program to apply their knowledge of the foundations, theory and methods of data science to address data driven problems in industry, government and the non-profit sector. The course activities focus on a semester-length project sponsored by a local organization. The project synthesizes the statistical, computational, engineering and social challenges involved in solving complex real-world problems. Typically, three or four students work together as a team on each project. Each team is supervised by a faculty mentor and projects typically progress through the following phases:
- Background and problem definition
- Data wrangling, munging and cleaning
- Exploratory Data Analysis
- Coding prototypes of algorithms and models
- Data Visualization
- Reporting and communicating
- Productionizing any models or algorithms if applicable
Outline of course
Students will meet as a cohort once a week where they will share best practices, and discuss relevant readings on topics including (1) entrepreneurship, (2) ethics, especially the ethics of mathematical models and algorithms, and (3) process and design thinking.
Please note: this information is subject to change based on the Faculty's discretion.
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