Hands-on Data Science
|Meeting Time:||I hr: TTh 10:30-11:50|
|Offered this year?||Yes|
|When Offered?||Every year|
Develops all aspects of the data science pipeline: data acquisition and cleaning, handling missing data, exploratory data analysis, visualization, feature engineering, modeling, interpretation, presentation in the context of real-world datasets. Fundamental considerations for data analysis are emphasized (the bias-variance tradeoff, training, validation, testing). Classical models and techniques for classification and regression are included (linear regression and logistic regression, support vector machines, decision trees, ensemble methods). Uses the Python data science ecosystem (numpy, pandas, matplotlib, scikit-learn).
Prerequisites: A course equivalent to CSCI 0050, CSCI 0150 or CSCI 0170 are strongly recommended.
Enrollment is limited to Data Science Master's program students.