Python for Data Science

3 units

Python has become the most popular programming language for data science and competency in Python is a critical skill for students interested in this area. This course introduces Python within the context of the closely related areas of statistics and data science. Topics include syntax and capabilities of Python, introduction to Spyder IDE and Jupyter notebooks, data wrangling using pandas library (cleaning, merging, reshaping, and summarizing/aggregating data), SQL databases, writing basic functions (handling missing data and common data cleaning tasks within the pandas framework), data visualization using Seaborn and Matplotlib, Statistical modeling with statsmodels, Machine learning with SKLearn (Tree Based Methods, Ensemble, SVM), Unsupervised Machine Learning with SkLearn (Clustering, K-means, Dimension Reduction, Principal Component Analysis), Introduction to NumPy, and Basics of Neural Network and PyTorch.