MBZUAI Online Screening Exam is a mandatory, proctored assessment designed to evaluate your foundational knowledge in Mathematics, Programming, and Machine Learning. The exam is fully automated, lasts approximately 45 to 60 minutes , and does use negative marking.
MBZUAI - Mohamed bin Zayed University of Artificial Intelligence 📐 Mathematics Section (40%)
This section focuses on the mathematical foundations required for Artificial Intelligence. Focus on conceptual understanding and geometric intuition.
MBZUAI - Mohamed bin Zayed University of Artificial Intelligence Linear Algebra
: Matrix operations, determinants, eigenvalues, eigenvectors, and solving systems of linear equations.
: Single and multivariate calculus, including limits, derivatives (chain rule), and optimization. Probability & Statistics
: Discrete and continuous distributions, Bayes' Theorem, mean, variance, and standard deviation. Optimization : Gradients, Jacobians, and Hessians.
MBZUAI - Mohamed bin Zayed University of Artificial Intelligence Sample Questions:
Find the probability that the sum of two rolled dice equals 7. Compute the determinant of a 3x3 matrix.
Find the probability that the second ball drawn from a bag (6 red, 2 blue) is red without replacement. 💻 Programming Section (40%) Most questions use
, but the focus is on algorithmic logic rather than specific language syntax. You may be asked to find the output of code or identify errors. Data Structures mbzuai entry exam sample questions best
: Basic understanding of Arrays, Stacks, Queues, Linked Lists, and Binary Trees. Algorithms
: Searching and sorting algorithms (e.g., Bubble Sort, Binary Search) and their time complexity.
: Recursion, loops, and Object-Oriented Programming (OOP) including classes and inheritance. Sample Questions:
What is the worst-case time complexity of searching a singly linked list of length
Write a Python function to check if a number is prime or a string is a palindrome.
Identify which WHILE loop produces the same output as a provided FOR loop. 🤖 Machine Learning Basics (20%)
This section tests your grasp of fundamental ML theory and model evaluation. Learning Paradigms
: Differences between supervised, unsupervised, and reinforcement learning. Model Theory
: Overfitting vs. underfitting, the bias-variance tradeoff, and gradient descent. Evaluation Metrics
: Confusion matrix, accuracy, precision, recall, and F1-score. Algorithms MBZUAI Online Screening Exam is a mandatory, proctored
: Key differences between Linear Regression and Logistic Regression. Sample Questions:
Gradient Descent computes the derivative of the loss function with respect to what? (Input, Weight, or Activation)
Explain how decision trees split data using Gini Index or Entropy. 🛠️ Preparation Resources & Tools Official Demo : A demo exam is provided within the Exam Portal software (use PIN: ) to help you test the interface.
: Search for "Mathematical for Machine Learning" or specific calculus/algebra tests. Learning Platforms : Courses on covering "Linear Algebra for ML" are highly recommended. Prep Guides : Third-party resources like the MBZUAI Master's Test Prep Guide offer up to 155 practice MCQs.
MBZUAI - Mohamed bin Zayed University of Artificial Intelligence 📋 Exam Day Checklist
: Use Windows 10/11 or macOS 10.15+. Google Chromebooks and Linux are supported. Environment
: A quiet, well-lit room. Your face must remain visible to the AI Proctor at all times.
: You are allowed blank paper, a pen, and a calculator (though minimal use is advised).
: Have a valid passport or government ID ready for the system's identity check.
MBZUAI - Mohamed bin Zayed University of Artificial Intelligence If you'd like, I can help you: Drill specific math topics like eigenvalues or probability. Practice Python coding for common data structures. Explain ML concepts like the bias-variance tradeoff in detail. subject area would you like to start with? MBZUAI Online Screening Exam Instructions It is required for MSc and PhD applicants
The MBZUAI entrance exam assesses foundational knowledge in:
It is required for MSc and PhD applicants (waivers possible for exceptional backgrounds). The exam is computer‑based, multiple‑choice, and typically 2–3 hours.
Many free resources online are too easy. MBZUAI questions are notoriously proof-heavy and conceptually deep. The "best" sample questions are those that require derivation, not just calculation. You need problems that test why an algorithm works, not just how to call sklearn.fit().
MBZUAI models its exam on:
Search for: "CS229 problem set 1 solutions" – these contain the exact proof-style linear algebra questions used by MBZUAI.
Before diving into the questions, you must understand the exam's philosophy. The MBZUAI entry exam is not an IQ test; it is a prerequisite audit. It assumes you have a Bachelor’s degree in Computer Science or Mathematics (or equivalent) and wants to ensure you can survive the first semester.
Key facts:
Warning: The "best" sample questions are useless if you ignore the time constraint. MBZUAI questions require deep reasoning, not speed-solving.
Focus: Gradients, Jacobians, Convexity, Lagrange Multipliers.
Sample Question 3 (Gradient Descent):
Consider the loss function ( L(w) = \frac12 ||y - Xw||^2 ). Compute the gradient ( \nabla L(w) ).
a) ( X^T (Xw - y) )
b) ( X^T y - X^T X w )
c) Both a and b are equivalent.
d) ( X X^T (y - Xw) )
Answer: (c). MBZUAI uses sign flips frequently. If you wrote ( X^T (Xw - y) ) during the exam, you are correct. They want to see if you understand that negative signs are algebraic, not mathematical errors.
