W1
Beginner
3 sessions · 6 hrs
Week 1: Python Fundamentals for Data Science
Installation, variables, data types, operators, control flow, functions, Git...
A complete 12-week curriculum from Python fundamentals to machine learning and capstone project development. Each week contains 3 sessions of 2 hours, with executable code examples, theory, and graded assignments. Built by Adeleke Akinrinade Kayode for professionals entering the UK and Nigerian data science job markets.
Installation, variables, data types, operators, control flow, functions, Git...
Lists, tuples, dictionaries, sets, list comprehensions, CSV file handling with the csv module...
DataFrame creation, reading CSV/Excel, exploration methods, boolean filtering, .loc[]/.iloc[], groupby aggrega...
Missing data mechanisms (MCAR/MAR/MNAR), imputation strategies, IQR and z-score outlier detection, winsorisati...
Skewness and kurtosis, bivariate analysis, matplotlib figure architecture, seaborn (histplot/boxplot/violinplo...
Probability axioms, conditional probability, Bayes theorem, Binomial and Normal distributions, Central Limit T...
Type I/II errors, p-values, one-sample t-test, independent t-test, ANOVA with Tukey HSD, chi-square test, Mann...
Pearson/Spearman correlation, partial correlation, VIF multicollinearity, OLS linear regression diagnostics, l...
Decision trees (CART, Gini impurity), Random Forest (bagging, feature importance), cross-validation (k-fold st...
K-means (algorithm, elbow method, silhouette score), hierarchical clustering (dendrogram, Ward linkage), DBSCA...
SQL fundamentals, JOINs, CTEs, window functions (ROW_NUMBER, RANK, LAG, LEAD), ARIMA model identification, sea...
CRISP-DM workflow, capstone project report structure, GitHub portfolio, UK/Nigerian CV for data scientists, te...
End-to-end project on a self-chosen real dataset. Full CRISP-DM cycle, GitHub repository, written report, and presentation. 30% of course grade.