Multivariable Calculus

TL;DR:

The rest of this post is going to talk about my experience taking MA 36200, and how I ended up producing the notes.

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Rewriting two posts

I started this blog as a freshman in college, wanting to jot down a, at the time, fascinating formula I derived to get around an asinine coding problem (which apparently, is still helpful to this day). I wrote multiple posts that essentially amounted to philosophy on how to be a good student/how not to be a good student, enchanted with the idea that I saw past the fog that no one else could.

I still think what I wrote then is true. Students, above all else, do a terrible job being honest with themselves. This goes in multiple directions, really. Poor professors and bad textbooks are just accepted without ever considering alternatives. Hundreds of textbooks are available online for any subject as well as the lecture notes and videos of other professors, yet go unused. Students also are not honest in what they do know and what they do not know, essentially wasting their time studying.

Okay. That’s the gist of it. Time to review some posts.

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MA 35100 Course Notes

I have just uploaded by MA 35100 course notes to the handouts page. Contrary to the page name, this is not a handout (and not something I would physically hand out, ever). These are not polished or edited; I welcome any and all suggestions and corrections. As a credibility statement, I finished the course with an A+.

25 pages are handwritten and makes the document quite large. I apologize.

As a note to those reading these notes that are taking MA 26500, this does not cover all topics in the MA265 curriculum (orthogonal bases). There’s also more proofs than the MA265 curriculum as well.

Demystifying the computer/data science CODO process

In recent semesters, an increasingly large number of students aim to CODO — Change of Degree Objective, essentially switching majors — into the Department of Computer Science to varying degrees of success. As someone who has successfully CODO’d into the Department of Computer Science to major in data science as well as being in contact with students that have attempted/are attempting to/have successfully CODO’d (both friends and students I have TA’d for), I have discussed the CODO process countless times. Misinformation has certainly been spread. In this post, I will detail the CODO requirements and give some commentary on how to increase one’s chances.

My information comes from two official sources: the College of Science’s Academic Advising’s CODO Requirements for 2019-2020 and the Department of Computer Science’s CODO Requirements.

[EDIT 2020 April 13]: I’d like to mention that outside of parts that make direct use of official sources, much of this blog post was written with some guess work. While I wrote this after having had successfully CODO’d into data science, I know more now than I knew then. Unfortunately, the things I have since learned and confirmed are not things I can make public, sorry.

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Talent is (often) an excuse

Whether or not you think talent exists, if someone brings up talent, it’s an excuse for something else.

[EDIT 2020 April 13:] I wrote this on a whim and very quickly. I add this disclaimer not as means to avoid being held accountable for my opinions but because I find that my prose and explanations were, frankly, not the best. I’d like to revisit this topic later.

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A Disgusting Function

I have a few friends in the engineering program at Purdue. They have to take a class called CS159, which formally teaches them the programming language C, presumably with its applications to engineering. I don’t really know the details, as I neither am in their program nor the class.

They had an assignment that revolves around a user selecting between three given formulas, inputting an argument and receiving the computed value. The catch? If-statements are entirely illegal. The majority of C is similarly off limits.

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