Data Science Fundamentals: Project Summaries¶

This site gives a simple overview of each project folder in this repository, based on the notebooks and README files.

At a Glance¶

Project	Main Analysis Used	Technologies / Methods
Profiling Academic Trajectories	Student-performance profiling, clustering, classification, interpretability	pandas, numpy, scikit-learn, scipy, plotly, matplotlib, shap, ucimlrepo
Life Expectancy Analysis	WHO data cleaning, missingness checks, clustering, PCA, map-based visualization	pandas, numpy, scikit-learn, plotly, missingno, pycountry, matplotlib
Data Analysis and k-NN	Supervised classification on Palmer penguins	pandas, numpy, scikit-learn, matplotlib, plotly, scipy
Data Analysis and PCA	Breast-cancer data preprocessing, scaling, PCA, k-NN baseline	pandas, numpy, scikit-learn, seaborn, matplotlib, plotly
Gradient Descent	1D and higher-dimensional gradient-descent experiments	numpy, plotly, IPython
Data Ethics Paper	Written ethics review of three readings	Comparative analysis, policy/ethics critique
Lecture Notes	Course demonstrations and experiments across core topics	pandas, numpy, scikit-learn, matplotlib, plotly, missingno

Project Pages¶

Use the navigation menu to open a page for each project.