Reply to Post No. 14718475

I have no idea what your final goals are, or what you are even studying specifically. That matters a lot unsurprisingly, consider including that next time. But basically, only you are capable of deciding whether you can achieve this or not. Even if the schedule is doable, it really is all up to you to follow through and stick to it. The schedule being realistic or not is pretty much irrelevant in this sense. A side note, some of the smartest people I know just aren't the type to ever do these sorts of cramming sessions, the weeks upon weeks of nothing but studying. They just integrate their areas of expertise into their daily lives (hobbies, media they consume, communities they interact with) with a little bit of talent, luck and a lot of passion. My point is, this is probably the most you can get away with without being unsustainable (i.e. potential burnout) and is by no means necessary to becoming an expert.

I wish I could give actual advice or a better answer here, but what you're seeking is essentially touching on whole fields of learning, test-taking, conducting research and getting ahead in your chosen areas. Like there isn't really a simple solution here (otherwise there wouldn’t be people spending their entire lives researching such things). Personally, I just think you shouldn't try to 'master' any given topic and just stop there, mastery is much more of a continuous and gradual process and concepts are all connected in some way. I'm still learning things about high-school level Math that are relevant to my current education despite having spent a good part of my life obsessing over Math Olympiads and getting the best scores I possibly can. Anki is really good for memorising things but different strokes for different folks, some enjoy gamifying everything they learn while others learn by doing. I guess just don't expect to remember everything or for things that you have managed to learn not to fade over time, you're basically building sandcastles here and they aren't going to last forever. Also, if you want to improve at a certain skill or just become smarter in general, don’t go about in a roundabout f*****g way. If you want to get better at Math, do more Math (I see your arithmetic over there, being a quasi-calculator is more of a party trick than anything btw, you don’t start spontaneously thinking any faster either). Don’t do Physics, don’t do Computer Science, learn more Math. If you want to have a more eloquent or sophisticated grasp of language, practice that. Likewise, becoming more creative when it comes to Math doesn’t rely on how imaginative you are in writing or drawing. It is, in some general IQ type sense but if you want to get good at something, don’t overly focus on complementary tasks that only serve to polish what you already have.

I’m already bored typing out this response so I’ll just end with some resources that helped me. https://refold.la/roadmap/stage-1/a/anki-setup for Anki settings, while you’re at it you should learn another language too (good for brain development). For general fitness (which is also good for brain development) I direct you to the /fit/ sticky (http://liamrosen.com/fitness.html). I’ve heard that neuron development is particularly stimulated by aerobic exercise but honestly just get any kind of routine and diet going first. Lately I have been working on improving my flexibility, yoga works as a resetting routine and flexibility exercise. If you are considering a job in academia, there are threads on this board for that (actually I should probably mention that the /sci/ sticky already has shit tons of useful information, reading that instead of this is *probably* a better use of your time).

Also, learn to code (especially if you want to go into academia). No buts, it is basically the baseline for digital literacy nowadays and is a great way to stand out. When starting out (I recommend Python or Java of course) I suggest learning as much of a programming language as you need at any given point. You won’t absorb good practices via osmosis so don’t try learning every feature at once; doing is also much more important for understanding than watching when it comes to programming as well (or pretty much anything you’ve mentioned). Look up some beginner projects and just start, it isn’t as bad as it seems. Also exercises, do them. The Euler project problem set requires a nice mix of CS and Math, I really like those (although I guess they aren’t exercises).

Textbooks can almost always be found at library genesis if you aren’t against pirating, just don’t start hording them like I do. Recommendations are easily found online (like /sci/ sticky or reddit), most people tend to mention the same titles so corroborate opinions and pick what seems good. Don’t read a book from front to cover, that’s a terrible way of learning and revisiting + nonlinear progression is something I always do (https://web.stanford.edu/class/ee384m/Handouts/HowtoReadPaper.pdf). General advice I enjoyed came from Evan Chen (https://web.evanchen.cc/) whose opinions I derived most of my own and Paul Graham's essays (https://www.paulgraham.com/articles.html). Common problems you may face are things like imposter syndrome or motivation. I personally struggle a lot with procrastination (possible a byproduct of years spent browsing mongolian basket weaving forums) and fairly frequently I see meta questions about dealing with these topics over at r/math.

Finally, uh, read often, don’t give up, talent matters but not so much that it excuses you from being the best person you can, make friends you can talk to about these things.
Sorry I actually just ended up ranting about my opinions which disguised as facts but I really related to your post, having felt and done that exact same thing (the ‘absolute mastery’ plus the scheduling thing) myself only a couple of years ago. I’m probably going to continue updating this pastebin now that I’ve started writing this, it is strangely enjoyable

Some extra sites I remember being favourites:
- http://www.catb.org/esr/faqs/smart-questions.html#intro
- https://sites.google.com/site/scienceandmathguide/subjects/mathematics     [/sci/ sticky]
- https://castel.dev/post/lecture-notes-1/
- https://ocw.mit.edu/course-lists/most-popular-courses/
- https://terrytao.wordpress.com/career-advice/
- https://freecomputerbooks.com/puremath.htm
- https://amctrivial.com/
- https://artofproblemsolving.com/community/c13_contest_collections