Mbzuai Entry Exam: Sample Questions Best
MBZUAI models its exam on:
MBZUAI - Mohamed bin Zayed University of Artificial Intelligence or a breakdown of the Machine Learning concepts often tested in the PhD stream? MBZUAI Online Entry Exam Guidelines
What is the time complexity of searching for an element in a balanced Binary Search Tree (BST) with nodes in the worst-case scenario?
(λ−5)(λ−2)=0open paren lambda minus 5 close paren open paren lambda minus 2 close paren equals 0 The eigenvalues are . Question 2: Find the gradient of the function at the point Solution: The gradient consists of the partial derivatives with respect to
Bayes' theorem, probability distributions, variance, and expectation. mbzuai entry exam sample questions best
To help tailor this advice to your specific background, what did you complete, and which specific AI program (Computer Vision, NLP, Machine Learning, etc.) are you applying for at MBZUAI? Share public link
Write a function reverse_linked_list(head) that takes the head of a singly linked list and returns the head of the reversed list.
The math section focuses on Linear Algebra, Calculus, Probability, and Statistics. MBZUAI favors questions that appear in Stanford’s CS229 or Andrew Ng’s deep learning specialization.
import numpy as np def stable_softmax(x): # x: (n, d) array # return: (n, d) array where each row sums to 1 MBZUAI models its exam on: MBZUAI - Mohamed
Which of the following is TRUE about Linear Regression and Logistic Regression?
Master the MBZUAI Entrance Exam: Sample Questions, Pattern, and Expert Preparation Strategy
Neural network with one hidden layer: Input ( x \in \mathbbR^d ), weight ( W_1 \in \mathbbR^h \times d ), bias ( b_1 ), ReLU activation, output weight ( w_2 \in \mathbbR^h ), sigmoid output. Derive the gradient of binary cross-entropy loss w.r.t ( W_1 ). Show dimensions at each step.
From a bag of 6 red and 2 blue balls, two balls are drawn consecutively without replacement. What is the probability that the second ball drawn is red? Question 2: Find the gradient of the function
: Understanding time complexity (Big-O notation), stacks, queues, and common sorting algorithms like Bubble Sort.
: Searching and sorting algorithms (e.g., Bubble Sort, Binary Search) and their time complexity.
Sample questions often cover fundamental concepts such as differentiating between linear and logistic regression and understanding that Gradient Descent optimizes weights by calculating the derivative of the loss function. 2. Mathematics & Linear Algebra