Applied Math for AI

MATH-1111 — Mastery Overview

2:10 PM - 5:00 PM
1
Linear Algebra Basics

Vectors, Matrices, and Linear Transformations.

Learning Outcomes:
• Perform matrix multiplication • Understand Geometric interpretation of vectors
2
Calculus & Derivatives

Introduction to the Power Rule and Chain Rule.

Learning Outcomes:
• Calculate partial derivatives • Understand the slope of cost functions
3
Gradient Descent Math

The mathematical foundation of optimization.

Learning Outcomes:
• Derive the update rule for weights • Calculate learning rate impact
4
Probability Theory

Random variables, distributions, and expectations.

Learning Outcomes:
• Calculate Gaussian distribution parameters • Understand Bayesian probability basics
Item Weight Raw Score Performance Status
Problem Set: Linear Algebra 10.00% 22 / 25
Graded
Problem Set: Derivatives 10.00% - Waiting for results... Pending
Midterm: Calculus Fundamentals 30.00% - Waiting for results... Pending
Assignment: Optimization Math 10.00% - Waiting for results... Pending
Final Cumulative Exam 40.00% - Waiting for results... Pending