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Expand Data Analysis Hard track content: more depth, examples, code #63

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@abderrahim-lectures

Substantially expands all 5 weeks of the Data Analysis Hard (EDA) track: more explanations (value_counts normalize, mean-vs-median skew reading, IQR outlier detection, bin-count sensitivity, correlation strength rules of thumb, hue for a third variable, pd.crosstab, row+col faceting, colorblind-safe palettes, plt.savefig, a full report-structure recap table with a second worked example), a Common Pitfalls section per week, and additional challenges/socratic questions/quiz questions per week. This completes the full course content expansion (all 20 weeks, both sections, both tracks).

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