Mastering Big O Notation

Looking back at the MITx 6.00x course, one concept that I continued to struggle with even in the final exam was Big O notation. The overall concept doesn’t give me any trouble. Professor Grimson is a superb lecturer who explained the idea clearly: Big O notation is used to compare the complexity of algorithms in terms of the relative time or memory it takes to run them in a worst case scenario (i.e. when you have ginormous input).

As I was going through the course, I watched the lectures on edX and an optional recitation posted on the MIT OpenCourseWare website. I got it … sorta. Continue reading “Mastering Big O Notation”

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Done with 6.00x

I just finished the final exam for 6.00x (Intro to CS and Programming), the MITx course I was taking in the fall. I have to admit that my stamina took a nosedive near the end of this course.

It’s really hard to keep up coursework over the holidays, and some hiccups in the course administration — mostly delays in getting new assignments posted — messed up my rhythm. So I put off doing the final problem set and watching the last couple sets of lectures until last week. And I have to admit something possibly scandalous: I didn’t bother finishing the final exam. Continue reading “Done with 6.00x”