I feel like point of lectures and classes, if you have a good professor/lecturer, is to be able to have the opportunity to understand how someone else understands a concept and is able to convey it to you. I personally think I did learn alot from passionate lecturers and professors, so I'd try to give some courses a chance, especially in upper levels when class sizes are smaller and curriculum is more specific (vs a intro to programming class, sure skip it if you know how for loops work)
The strategy itself is pretty nifty though, I feel like lecture notes with no person speaking behind it are very dry and content light, so claude being able to read it and probably look at external references to populate a study guide is pretty smart.
I was in a situation where my CS degree was not challenging, so I decided taking graduate classes, and then branching out to courses offered by the Maths department both undergrad and graduate classes. I took many proof heavy courses in both departments, and I don't think you can get away with passing courses without putting in the effort of doing homework, attending lectures, and getting deeply involved with the courses. I feel this guy is just wasting his money.
I realized too late that my top CS program wasn’t challenging enough. If I did it again, I would have taken some grad classes and lean heavily in to upper division math classes, or maybe go for a physics minor, but I was so interested in coasting during my early 20s. Many classmates did that and got much more out of their undergrad (one classmate double majored in math and became a professor at UIUC after grad school).
One of my favourite memories branching out was taking an intro to abstract algebra course where the professor was in his 90s and a WW2 vet which left a lifelong impression. Was such a fantastic course and essential to honing my proof writing skills.
If you can get away with this, keep doing so, but definitely recommend putting some time into the 59000 / 69000 classes taught at the grad level.
Advisors let you swap elective classes in your track for the higher level ones, and they’re far more interesting (especially for the AI/ML track).
Also connects you with more professors that would be research oriented (if that was something you were interested in).
The program also had an exchange with ETH/KTH which unfortunately I couldn’t take advantage of due to COVID.
> I’m a decent test-taker and code a lot, so most concepts aren’t new. I rarely attend lectures and do the bare minimum homework required to pass. My broad curiosity gives me wide, shallow knowledge. Interestingly, I enjoy taking tests, especially multiple-choice.
This also worked for me. I did however go to the classes I liked and replaced steps 1-6 with cramming for several hours the night before.
I'm doing the same kind of thing for my college classes no matter the subject. But mine is a little different. Instead I do:
1. Feed lecture slides, labs, homework into ChatGPT and have it generate flashcards.
2. Write these flashcards into Anki and study them using Anki.
3. Run through some practice problems
I had originally intended for this system to be used long-term, but I get irresponsible and study the day of the exam. It really depends on the material, but for the most part, it takes around 5–7 hours of studying and preparation to feel completely confident about the exam. Often times, I wake up super early on the exam day to give me some time. This is not ideal of course and is just a product of my bad habits.
It's definitely doable to ace exams with only 2–3 of studying, but usually I need to pad it with another 2–3 hours of preparation like creating high quality flash cards and stuff. I believe most people can adopt this system and perform very well, but at the same time it's a very radical departure from traditional study practices and even then I'm not even using this system in the way it's actually intended (not the day of cramming-style method).
This system is not something I made up, but rather backed from a collective community effort that has produced amazing techniques, guides, research, etc.:
https://thehardway.guide/ - a damn good book teaching about actionable and pragmatic advice about language learning that i've applied to all of my college courses
I never really understood the point of anki outside of vocabulary learning. I would be happy to have it explained to me. Even when learning a language, I found anki to be a bit useless since often times the grammar was as important to learn (e.g., any language with genders and cases). Like I guess I don't see how anki would help me be the scientist I am today, how it might help me learn new topics that I am interested in to pursue new research directions. I am not against anki, I simply don't see how it would benefit me although if you could explain it to me I am all ears.
In particular I liked the section partway* through the article where he talks about using Anki to get up to speed on the AlphaGo paper for an article he was writing for Quanta.
It's great for learning the Ham radio test answers (publicly available), Major System, and NATO Phonetic Alphabet. I did not particularly enjoy Anki when I first tried it for Japanese-learning. I also found using it on my phone (AnkiDroid from F-Droid) worked better since I could grind it out anywhere I was. I never used their sync thing, IIRC it's proprietary. I also had success once using it to study for a technical interview (tech support, not programming, mostly shell commands and important paths).
I stopped using it a couple phones ago when the app seemed to break after trying to copy over my data. I've had several incidences since where I regretted not knowing the Major System well anymore, as I ran into a long number it'd be useful to memorize for a bit. I mostly used public decks I downloaded, though I did make my own for the interview study.
Whoa—you can't post racial/national putdowns to HN.
I realize you might not have meant it that way, but given a large audience like HN, a comment like this is guaranteed to land that way with some readers, and some of those readers will be activated enough to comment angrily, then we fall into flamewar hell. So if you could please not post like this, we'd be grateful.
I feel like point of lectures and classes, if you have a good professor/lecturer, is to be able to have the opportunity to understand how someone else understands a concept and is able to convey it to you. I personally think I did learn alot from passionate lecturers and professors, so I'd try to give some courses a chance, especially in upper levels when class sizes are smaller and curriculum is more specific (vs a intro to programming class, sure skip it if you know how for loops work)
The strategy itself is pretty nifty though, I feel like lecture notes with no person speaking behind it are very dry and content light, so claude being able to read it and probably look at external references to populate a study guide is pretty smart.
I was in a situation where my CS degree was not challenging, so I decided taking graduate classes, and then branching out to courses offered by the Maths department both undergrad and graduate classes. I took many proof heavy courses in both departments, and I don't think you can get away with passing courses without putting in the effort of doing homework, attending lectures, and getting deeply involved with the courses. I feel this guy is just wasting his money.
I realized too late that my top CS program wasn’t challenging enough. If I did it again, I would have taken some grad classes and lean heavily in to upper division math classes, or maybe go for a physics minor, but I was so interested in coasting during my early 20s. Many classmates did that and got much more out of their undergrad (one classmate double majored in math and became a professor at UIUC after grad school).
One of my favourite memories branching out was taking an intro to abstract algebra course where the professor was in his 90s and a WW2 vet which left a lifelong impression. Was such a fantastic course and essential to honing my proof writing skills.
Chiming in with a Purdue alum perspective.
If you can get away with this, keep doing so, but definitely recommend putting some time into the 59000 / 69000 classes taught at the grad level. Advisors let you swap elective classes in your track for the higher level ones, and they’re far more interesting (especially for the AI/ML track). Also connects you with more professors that would be research oriented (if that was something you were interested in). The program also had an exchange with ETH/KTH which unfortunately I couldn’t take advantage of due to COVID.
Step -1:
> I’m a decent test-taker and code a lot, so most concepts aren’t new. I rarely attend lectures and do the bare minimum homework required to pass. My broad curiosity gives me wide, shallow knowledge. Interestingly, I enjoy taking tests, especially multiple-choice.
This also worked for me. I did however go to the classes I liked and replaced steps 1-6 with cramming for several hours the night before.
I mean the guy states that the concepts aren't new to him. If you start from there then most people wouldn't need to study very much.
I'm sure as a graduate I could go back, not study and score well.
If you've never heard of it before then it's going to take a lot more effort to understand.
I'm doing the same kind of thing for my college classes no matter the subject. But mine is a little different. Instead I do:
1. Feed lecture slides, labs, homework into ChatGPT and have it generate flashcards.
2. Write these flashcards into Anki and study them using Anki.
3. Run through some practice problems
I had originally intended for this system to be used long-term, but I get irresponsible and study the day of the exam. It really depends on the material, but for the most part, it takes around 5–7 hours of studying and preparation to feel completely confident about the exam. Often times, I wake up super early on the exam day to give me some time. This is not ideal of course and is just a product of my bad habits.
It's definitely doable to ace exams with only 2–3 of studying, but usually I need to pad it with another 2–3 hours of preparation like creating high quality flash cards and stuff. I believe most people can adopt this system and perform very well, but at the same time it's a very radical departure from traditional study practices and even then I'm not even using this system in the way it's actually intended (not the day of cramming-style method).
This system is not something I made up, but rather backed from a collective community effort that has produced amazing techniques, guides, research, etc.:
https://isaak.net/mandarinmethods/ - in depth guide detailing best practices with Anki regarding language learning (THE BEST)
https://cademcniven.com/posts/20211119/ - recommended number of cards per day to study based on some grassroots research
https://github.com/open-spaced-repetition/fsrs4anki - the most modern spaced repetition algorithm which uses machine learning to optimize for each individual's learning capabilities (THE BEST)
https://www.reddit.com/r/Anki/comments/18jvyun/some_posts_an... - meta resource on fsrs
https://www.justinmath.com/individualized-spaced-repetition-... - a reading which i've incorporated into the way i create flash cards pertaining to more problem-solving type of learning as opposed to pure memorization like facts about history
https://thehardway.guide/ - a damn good book teaching about actionable and pragmatic advice about language learning that i've applied to all of my college courses
I never really understood the point of anki outside of vocabulary learning. I would be happy to have it explained to me. Even when learning a language, I found anki to be a bit useless since often times the grammar was as important to learn (e.g., any language with genders and cases). Like I guess I don't see how anki would help me be the scientist I am today, how it might help me learn new topics that I am interested in to pursue new research directions. I am not against anki, I simply don't see how it would benefit me although if you could explain it to me I am all ears.
You might find this article by Michael Nielsen interesting: https://augmentingcognition.com/ltm.html
In particular I liked the section partway* through the article where he talks about using Anki to get up to speed on the AlphaGo paper for an article he was writing for Quanta.
* Do a Ctrl-F for "AlphaGo"
He also writes here about how to use spaced repetition to see through a piece of mathematics: https://cognitivemedium.com/srs-mathematics
It's great for learning the Ham radio test answers (publicly available), Major System, and NATO Phonetic Alphabet. I did not particularly enjoy Anki when I first tried it for Japanese-learning. I also found using it on my phone (AnkiDroid from F-Droid) worked better since I could grind it out anywhere I was. I never used their sync thing, IIRC it's proprietary. I also had success once using it to study for a technical interview (tech support, not programming, mostly shell commands and important paths).
I stopped using it a couple phones ago when the app seemed to break after trying to copy over my data. I've had several incidences since where I regretted not knowing the Major System well anymore, as I ran into a long number it'd be useful to memorize for a bit. I mostly used public decks I downloaded, though I did make my own for the interview study.
Actual secret trick: learn next years course this year. It takes 6-12 months for neurons to mature in a human brain.
Remember how easy last years math was the next year?
it's Purdue... it's a good school no doubt but this guy acts like he's acing things at MIT or Stanford... c'mon.
Is the curriculum that different? The fundamentals are the same no matter where you go.
Title just sounds better that way.
The best part about Purdue is that I can use “top CS school” and “random state school” depending on which sounds better.
[dead]
[flagged]
Whoa—you can't post racial/national putdowns to HN.
I realize you might not have meant it that way, but given a large audience like HN, a comment like this is guaranteed to land that way with some readers, and some of those readers will be activated enough to comment angrily, then we fall into flamewar hell. So if you could please not post like this, we'd be grateful.
https://news.ycombinator.com/newsguidelines.html
Better word is “bay area”.
?