MS-DS Master of Data science Study Guide 2026

Everything you need to pass the MS-DS Master of 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.

📋 MS-DS Master of Data science Exam Format at a Glance

60
Questions
60 min
Time Limit
70%
Passing Score

📚 MS-DS Master of Data science Topics to Study (57)

Big Data · 16 cardsMachine Learning · 16 cardsNatural Language Processing · 16 cardsMaster of Data Science · 16 cardsResearch & Data Analysis · 16 cardsStatistical Inference & Regression Models · 16 cardsFeature Engineering · 7 cardsFeature Engineering · 7 cardsFeature Engineering · 7 cardsBig Data Technologies · 6 cardsData Visualization and Communication · 6 cardsData Wrangling and Preprocessing · 6 cardsStatistical and Probabilistic Analysis · 6 cardsUnsupervised Machine Learning Models · 6 cardsData Wrangling and Preprocessing · 6 cardsDeep Learning and Neural Networks · 6 cardsDeep Learning and Neural Networks · 6 cardsDeep Learning and Neural Networks · 6 cardsExploratory Data Analysis · 6 cardsFREE Master of Data science Big Data Questions and Answers · 6 cardsFREE Master of Data science Big Data Questions and Answers · 6 cardsFREE Master of Data Science Machine Learning Questions and Answers · 6 cardsFREE Master of Data Science Machine Learning Questions and Answers · 6 cardsFREE Master of Data Science Natural Language Processing Questions and Answers · 6 cardsFREE Master of Data Science Natural Language Processing Questions and Answers · 6 cardsFREE Master of Data Science Questions and Answers · 6 cardsFREE Master of Data Science Questions and Answers · 6 cardsFREE Master of Data Science Research & Data Analysis Questions and Answers · 6 cardsFREE Master of Data Science Research & Data Analysis Questions and Answers · 6 cardsFREE Master of Data Science: Statistical Inference & Regression Models Questions and Answers · 6 cards

✍️ Sample MS-DS Master of Data science Questions & Answers

1. What is the purpose of A/B testing in a data-driven organization?
To compare two versions of a variable to determine which performs better

A/B testing is a controlled experiment where two variants are compared to measure which one produces a better outcome on a specific metric.

2. Which of the following suggests there is no association between any of the relationships?
Cor(X, Y) = 0

The correlation coefficient, Cor(X, Y), measures the strength and direction of the linear relationship between two random variables X and Y. A value of 0 indicates that there is no linear association between the variables. It's important to note that a correlation of 0 does not necessarily imply independence, as non-linear relationships might still exist.

3. The problems with big data veracity go beyond volume, diversity, and velocity.
True

The '3 V's' (Volume, Velocity, Variety) are commonly associated with Big Data, but 'Veracity' is a fourth crucial dimension. Veracity refers to the trustworthiness, accuracy, and quality of the data, addressing issues like bias, noise, and abnormalities that can significantly impact analysis and decision-making.

4. In maximum likelihood estimation, what is the Fisher information used to approximate?
The variance of the MLE asymptotically

The inverse of the Fisher information provides the asymptotic variance of the MLE, forming the basis of the Cramér-Rao lower bound.

5. The degrees of freedom in the Chi-squared distribution are twice as many.
variance

For a Chi-squared distribution, the degrees of freedom (often denoted as 'k') define its shape and properties. The mean of a Chi-squared distribution is equal to its degrees of freedom (k), and its variance is equal to twice its degrees of freedom (2k). Therefore, the degrees of freedom are directly related to, and half of, the variance.

6. Which unsupervised learning technique reduces dimensionality by finding orthogonal axes that maximize variance in the data?
Principal Component Analysis (PCA)

PCA identifies principal components as orthogonal directions of maximum variance, enabling dimensionality reduction while preserving the most information.

🎯 Free MS-DS Master of Data science Practice Tests

📖 MS-DS Master of Data science Guides & Articles

Your MS-DS Master of Data science Study Path
1. Learn with Flashcards → 2. Drill Practice Tests → 3. Take the Full Exam Simulation