Exam Review; Algorithm - Design & Analysis Part 2
Hola everyone!
It's a me, Filippo! (from Italy as you, obviously, damn mustached plumper)
Finally, i've ended another exam, and it was a tough one, the second (and last) part of the Design & Analysis of Algorithm done by Stanford (here)
The course covers the topics listed above during the span of 6 weeks, which is fair, in my opinion. Using less weeks makes the entire thing too challenging, and diluite it in more becomes too "redundant"
I really like how Tim RoughGarden sets his lectures. The speaking is really easy to listen for a non-native english speaker. The videos are usually from 5 to 14 minutes long, which is a manegable length, so you don't lose the focus. Topics covered are, usually, the algorithms and (you don't say) their mathematical analyses, nothing really too fancy, but straight to the point.
The exercises are usually algorithms studied during the course, but the input size is really, really big. Due to that, many times you can't simply complete the task, so you need to look back at what you've wrote, and try to lower the runtime, which isn't something really that easy, but it's probably the most important thing in the whole course
But i got that. 70%. Enough for a statement, so i got it.
Brilliant course as usual, Stanford, keep'em coming. 8,5/10
See you with the next article :)
It's a me, Filippo! (from Italy as you, obviously, damn mustached plumper)
Finally, i've ended another exam, and it was a tough one, the second (and last) part of the Design & Analysis of Algorithm done by Stanford (here)
Course Overview
The course i took is literally the same i previously started on coursera, but with a substantial difference. The OpenEdx platform, compared to the one built by Andrew Ng, was more challenging, leaving only 2 tries for each theory question and 10 trials for the practice programming exercises, which are notoriously hard (mainly due to the size of the input). The second part f the course covert MST (minimum spanning trees), dynamic programming, SSSP and APSP, NP-complete problems and heuristic. The MOOC has also a final exam, which covers all the material previously seen. The course instructor is tim roughgarden, which is a great tutor imo, as altready discussed.The course covers the topics listed above during the span of 6 weeks, which is fair, in my opinion. Using less weeks makes the entire thing too challenging, and diluite it in more becomes too "redundant"
I really like how Tim RoughGarden sets his lectures. The speaking is really easy to listen for a non-native english speaker. The videos are usually from 5 to 14 minutes long, which is a manegable length, so you don't lose the focus. Topics covered are, usually, the algorithms and (you don't say) their mathematical analyses, nothing really too fancy, but straight to the point.
Programming Assignment
Stanford's Programming assignments are, as i've already said, really challening.The exercises are usually algorithms studied during the course, but the input size is really, really big. Due to that, many times you can't simply complete the task, so you need to look back at what you've wrote, and try to lower the runtime, which isn't something really that easy, but it's probably the most important thing in the whole course
Final Exam & Conclusions
The final was (for me, at least) not a joke. 20 questions, multiple choices. As a standard university exam, and you bet, same challenging level (even more).But i got that. 70%. Enough for a statement, so i got it.
Brilliant course as usual, Stanford, keep'em coming. 8,5/10
See you with the next article :)
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