Courses taken during my current undergraduate degree. I started the University of Waterloo in Computer Engineering in 2017 and switched to the faculty of Mathematics to pursue a major in Statistics and minor in Computer Science in Fall, 2019.
Expected Graduation Date: April, 2022
Expected Degree: Bachelor of Mathematics in Statistics with Minor in Computer Science
Semsters:
- Fall Term: Sept - Dec
- Winter Term: Jan - Apr
- Spring term: May - Aug
Course List by Semester:
Fall, 2017
- ECE 150: Fundamentals of Programming
- ECE 105: Classical Mechanics
- ECE 190: Engineering Profession and Practice
- CHE 102: Chemistry for Engineers
- MATH 115: Linear Algebra
- MATH 117: Calculus 1 for Engineering
Winter, 2018
- PD 20: Engineering Workplace Skills I: Developing Reasoned Conclusions
- CO-OP 1: Technical Operations Intern @ Interset
Spring, 2018
- ECE 124: Digital Circuits
- ECE 140: Linear Circuits
- ECE 108: Discrete Mathematics
- ECE 106: Electricity and Magnetism
- Math 119: Calculus 2 for Engineering
Fall, 2018
- PD 21: Engineering Workplace Skills II: Developing Effectve Plans
- CO-OP 2: Data Analyst @ HelloGbye
Winter, 2019
- ECE 204: Numerical Methods
- ECE 240: Electronic Circuits
- ECE 222: Computer Design and Organization
- ECE 250: Algorithms and Data Structures
- ECE 205: Advanced Calculus 1 for Engineers
- ECE 290: Engineering Profession, Ethics, and Law
Spring, 2019
- PD 3: Communication
- CO-OP 3: Python NLP Intern @ Loom Analytics
Fall, 2019
- STAT 240: Probability (Advanced)
- MATH 235: Linear ALgebra 2
- MATH 237: Calculus 3
- MATH 135: Introduction to Algebra
- SPCOM 100: Interpersonal Communication
- PD 11: Technical Report Writing
Winter, 2020
- STAT 241: Statistics (Advanced)
- STAT 333: Applied Probability
- CS 245: Logic and Computation
- CS 246: Object-Oriented Software Development
Fall, 2020
- STAT 341: Computational Statistics and Data Analysis
- STAT 330: Mathematical Statistics
- CS 240: Data Structures and Data Management
- STAT 331: Applied Linear Models
- MATH 239: Intro to Combinatorics
Winter, 2021
- STAT 441: Stastical Learning - Classification
- STAT 440: Computational Inference
- CS 332: Sampling and Experimental Design
- CS 341: Algorithms
- CO 227: Introduction to Optimization