Curriculum

Erik Mattson

Academic Portfolio

Curriculum

Calculus I & II: - I did not enjoy math much in high school. It was incredibly dull. I only took up to probability and statistics before. I took a quick online course at my community college to prepare me for the placement exam so that I could start in Calculus. It was a whole new game. Each day I learned new stuff, and most of it felt very useful. It wasn't easy, but I had a great time in these two classes.

I should Mention that I was majoring in data science at this point. I won't mention my CS courses here, but they were a huge let-down from my expectations, whereas the math courses were high quality.
Introduction to Probability Theory: - My first major-specific course. The first half was mostly events, set theory, and other discrete events. This was some of the most fun that I had so far in school. The problems all felt like little puzzles at the time.

The second half of the semester revolved around the probability distributions. This got dull rather quickly. All of them were different, but if you can work with one distribution, you can work with almost any other.
Linear Algebra: - There isn't really anything to say about this course. It was good, albeit hard at times, and I learned a lot of useful things.

These two courses together really showed me how much fun math was, so I ended up making the switch to applied statistics. It was also around this time where I became a math tutor for the school.
Calculus III: - Between this semester and the last, I learned almost all of the concepts in this class before they were taught. Most of the class felt like it was just calculus I and II, but with extra dimensions.
Statistical Methods II: - Don't ask me why the course has a II in it. Nobody knows. This was very much a core class, handling a large portion of statistics. The only notable parts were on minimum variance unbiased estimators (MVUE) and maximum likelihood estimation (MLE). These two concepts came one after another and took a lot of practice to understand but are quite cool concepts. In general, I don't think I enjoy statistics as much as probability.
Multivariate Distributions: - Stochastic Processes but easier and with a few extra concepts.
Stochastic Processes: - I thought it would be fun to take a senior level course. And while it was a blast, boy was it hard. The homeworks were time consuming, difficult, and very rewarding, as Sheldon Ross textbooks tend to be.

We covered discrete and continuous-time Markov chains, exponentials, Poisson processes, stationary processes, and others.

While I was in class with people who were here for their last semester, it really felt like the fun was just beginning.
Differential Equations: - Left a lot to be desired. I learned about differential equationsin the first two weeks, but the rest of the class was just about how to solve specific types.
Mathematical Modelling: - A class intended for Softmores. Introduced me to a lot of concepts that I unfortunately already learned. Made a physics-based model for my midterm and an agent-based predator-prey model for my final. Used Matlab.
Applied Numerical Methods: - It's a course on applied Taylor series. Very uninteresting to me. Used MatLab.
Regression Analysis: - Literally just a course on linear regression. Homework used R software.
Intro to Math Analysis: - One of the few "pure" math classes offered at this school. It coveres more or less Calculus I and II. I didn't really care too much for the concepts, but I found the problems fun and challenging.
Applied Time Series Analysis: -
Stat Methods in Data Sci: -
Advanced Calculus: -
Linear Algebra and Applications: -
Applied Statistics: -