Data Science with Python Certification Cheat Sheet 2026

The 30 highest-yield Data Science with Python Certification facts, distilled from real exam questions. Print it, save it as a PDF, or study it here — free, no sign-up.

1. Which step in the Expectation-Maximization (EM) algorithm computes the probability of each point belonging to each cluster? → E-step (Expectation)
2. Which forecasting model captures both trend and seasonality using exponential smoothing? → Holt-Winters model
3. What does df.astype({'age': 'int32', 'score': 'float32'}) accomplish? → Casts the specified columns to new data types to reduce memory usage
4. Which statistical method measures the linear relationship strength between two continuous variables? → Pearson correlation coefficient
5. In seaborn, which plot type is most appropriate for visualizing the distribution of a single continuous variable? → sns.histplot()
6. In feature engineering, what is 'weight of evidence' (WoE) encoding primarily used for? → Encoding categorical variables for binary classification
7. What is a confidence interval in statistics? → A range likely to contain the true population parameter
8. Which Python function calculates the standard error of the mean? → scipy.stats.sem()
9. When using `sklearn.decomposition.PCA`, what does `explained_variance_ratio_` return? → The fraction of total variance explained by each principal component
10. What does `df.groupby('category').mean()` compute in pandas? → The mean of all numeric columns grouped by unique values in 'category'
11. In spaCy, what attribute of a `Token` object returns its part-of-speech tag? → token.pos_
12. What does Python's "capture" cell magic command not support? → It cannot be used to capture graphical cell output
13. In Matplotlib, which function saves the current figure to a file? → plt.savefig()
14. In Matplotlib, which method saves the current figure to a file? → plt.savefig()
15. What does the PACF (Partial Autocorrelation Function) help determine in ARIMA modeling? → The AR (p) order
16. What is the output dtype of np.array([1, 2.0, 3])? → float64
17. What is the purpose of a learning curve in model evaluation? → To diagnose whether a model suffers from high bias or high variance
18. What does `np.where(condition, x, y)` return? → Elements from x where condition is True, otherwise from y
19. Choose a non-indexed object. → None of these
20. Which pandas dtype is assigned to a column containing text strings by default? → object
21. What is the output of np.array([1,2,3]).reshape(3,1).shape? → (3,1)
22. Which of the following is NOT a valid initialization strategy for K-Means in scikit-learn? → 'ward'
23. How do you add a title to a Matplotlib subplot using the axes object 'ax'? → ax.set_title('My Title')
24. What does the cophenetic correlation coefficient measure in hierarchical clustering? → How faithfully the dendrogram preserves pairwise distances
25. When using sklearn's train_test_split, what does the stratify parameter do? → Preserves the class distribution in both train and test sets
26. In pandas, what does df.duplicated().sum() compute? → The total number of duplicate rows in the DataFrame
27. What does the following Python code produce? a, b = 0, 1 while b print(b, end=' '); a, b = b, a+b → 1 1 2 3 5 8 1 3
28. Which algorithm would be most suitable for a dataset with 1 million samples and 500 features where training speed is critical? → Stochastic Gradient Descent Classifier
29. What is broadcasting in NumPy? → Performing element-wise operations on arrays of different shapes
30. When analyzing a dataset for outliers using the IQR method, which values are typically flagged? → Values below Q1 - 1.5*IQR or above Q3 + 1.5*IQR