The math section evaluates your fluency in fields critical to machine learning. Focus on , Calculus , and Probability .

Sample: "Gradient Descent computes the derivative of the loss function with respect to (A) Input, (B) Activation value, or (C) Weight?" (Correct: Weight).

Some versions of the exam include brain teasers or "common sense" logic problems.

: Be ready for pseudo-code questions involving while loops, modulus operators, and recursion.

: Review basics like activation values and loss functions. 4. Logical & Analytical Thinking

For MSc and PhD applicants, the exam tests your conceptual understanding of AI models.

: Focus heavily on Linked Lists , including how to traverse them or print all data within a Python function.

: Know the "worst-case" time complexity for common operations, such as searching a linked list ( ) or Merge Sort ( 3. Machine Learning Basics