Data Science Study Guide 2026

Everything you need to pass the Data Science exam in one place: the exam format, every topic to study, real practice questions with explanations, flashcards, and full-length practice tests. Free, no sign-up needed.

📋 Data Science Exam Format at a Glance

Questions

60 min

Time Limit

70%

Passing Score

Take a Full Data Science Exam Simulation →

📚 Data Science Topics to Study (107)

Analysis · 7 cards Analysis · 7 cards Analysis · 7 cards Analysis · 7 cards Data Cleaning and Preparation · 7 cards Data Cleaning and Preparation · 7 cards Data Cleaning and Preparation · 7 cards Data Cleaning and Preparation · 7 cards Data Science MCQ · 7 cards Data Science MCQ · 7 cards Data Science MCQ · 7 cards Data Science MCQ · 7 cards Data Visualization and Communication · 7 cards Data Visualization and Communication · 7 cards Data Visualization and Communication · 7 cards Data Visualization and Communication · 7 cards Data Wrangling and Preprocessing · 7 cards Data Wrangling and Preprocessing · 7 cards Data Wrangling and Preprocessing · 7 cards Data Wrangling and Preprocessing · 7 cards Feature Engineering and Selection · 7 cards Feature Engineering and Selection · 7 cards Feature Engineering and Selection · 7 cards Feature Engineering and Selection · 7 cards Model Evaluation and Validation · 7 cards Model Evaluation and Validation · 7 cards Model Evaluation and Validation · 7 cards Model Evaluation and Validation · 7 cards Model Performance and Evaluation · 7 cards Model Performance and Evaluation · 7 cards

See all 107 topics as flashcards →

✍️ Sample Data Science Questions & Answers

1. What is multicollinearity in a regression model?

✓ High correlation among predictor variables

Multicollinearity occurs when independent variables are highly correlated with each other.

2. When splitting data into training and test sets, why should stratified sampling be used for imbalanced classification problems?

✓ To ensure both sets maintain the same class distribution as the original data

Stratified sampling preserves the original class proportions in both splits, preventing situations where the minority class is underrepresented or absent in one set.

3. Combining two DataFrames on a shared key column in pandas is done with:

✓ pd.merge()

pd.merge joins DataFrames on common key columns.

4. When you send a MapReduce task to a Hadoop cluster, you discover that even though it was sent successfully, the job has not yet been finished. What ought you to do?

✓ Ensure that the TaskTracker is running

In older Hadoop 1.x architectures, the TaskTracker was responsible for executing individual Map and Reduce tasks on the data nodes. If a MapReduce job has been successfully sent but is not finishing, it indicates that the tasks themselves are not being executed. Therefore, ensuring the TaskTracker (or its equivalent, the NodeManager in Hadoop 2.x+) is running is crucial for job execution.

5. Which dimensionality reduction technique is unsupervised and linear?

✓ Principal Component Analysis (PCA)

PCA is an unsupervised, linear method that projects data onto directions of maximum variance.

6. In a neural network, what is the role of the activation function?

✓ To introduce non-linearity into the model

Activation functions like ReLU or sigmoid introduce non-linearity, allowing neural networks to learn complex, non-linear relationships that a purely linear model could not capture.

🎯 Free Data Science Practice Tests

Statistical Concepts and Inference · 7 questions Statistical Concepts and Inference · 7 questions Statistical Concepts and Inference · 7 questions Statistical Concepts and Inference · 7 questions Data Visualization and Communication · 7 questions Data Visualization and Communication · 7 questions Data Visualization and Communication · 7 questions Data Visualization and Communication · 7 questions Feature Engineering and Selection · 7 questions Feature Engineering and Selection · 7 questions

📖 Data Science Guides & Articles

Your Data Science Study Path

1. Learn with Flashcards → 2. Drill Practice Tests → 3. Take the Full Exam Simulation

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