Progress:
- Programming Abstractions: Watched through lecture 7.
- Lots of interesting new data types being introduced. It's largely stuff that's part of the course-specific libraries, but nonetheless a lot of it looks interesting. Basically I'm seeing counterparts to a lot of the fundamental data types that are included in python like lists ("vectors" in this class) and dictionaries ("maps"), and some new data types like the LIFO-vector type "stack" and the FIFO-vector "queue", as well as a fast-access unstructured array called the "set." The lecturer gives good examples of all of them, and I wonder if I might at some point find C++ as easy or easier for certain things than python.
- Algorithms: Watched through the third video of section 9.
- More operations on arrays, namely selection algorithms (such as the canonical "find the ith smallest member of a set") and graph theory (minimum cut problem) that both make use of randomized algorithms, much like the QuickSort algorithm.
- Linear Algebra: Watched lecture 6.
- With the somewhat tedious subject of manipulating matrices seemingly covered, it seems we're ready to dive into the more theoretical concepts in linear algebra. He started talking about subspaces of a space, which is an interesting topic and one that is perhaps ironically much easier for me to grasp than figuring out how one matrix will multiply another - although I'm getting better at that too.
- Udacity 101: Watched final 2 units of the course. Took the final exam, minus the starred problems.
- The final part, which was an explanation of Google's PageRank algorithm, left me somewhat confused. I feel like the explanation of the derivation of the terms in the algorithm was presented very quickly and without adequate time spent on saying what each term was doing and why the equation had the composition that it did in the end. I might rewatch them to see if I get a better idea upon second (more like third) viewing. Otherwise, the class was lots of fun and I'm glad I took it. I felt that the final exam was pretty easy, although I haven't tried the starred (bonus) problems. The first starred problem on the final exam looks quite a bit like some of the graph theory we're being introduced to in algo. I might give those problems a try, though time constraints might prevent me.
- GRE study: began some practice problems in the vocabulary and reading comp sections.
- The reading comp problems are really unnecessarily weasely in my opinion. They're worded like riddles and that seems to be their primary value (although, for riddles, they're hardly amusing). I suppose a law student would be expected to ace that kind of thing, as the sort of subtle differences it's asking you to identify is the kind of thing that in my opinion would really only be relevant if you're looking for loopholes in legal language or some other kind of quibbly pursuit.
To do next:
- Programming Abstractions: at least get started on problem set 2.
- Algorithms: problem set 3 is due tomorrow, and there are also a few lectures I still need to watch to cover the proper material.
- Linear Algebra: get started on problem set 2, read appropriate sections of the book
- GRE: more practice problems. Try writing some of the essays. Get registered for the real thing next month.
- Figure out what course is going to take the place of the Udacity course. It's somewhat of a moot point as there will be a whole host of new classes starting around April 16th, but nonetheless. Perhaps the discrete math would be a good fit for this, or I could simply decide to use the time towards existing classes.
- Finish the FreeCell game, at least up to the point of a text-based implementation.
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