I have a long-term goal of acquiring graduate-level knowledge in Analysis, Algebra and Geometry/Topology. Once that is achieved, I am interested in applying this knowledge to both pure and applied mathematics. In particular, I am interested in various aspects of smooth manifolds, co/homology and mathematical physics. I have acquired a smattering of knowledge in all of these areas but feel that I need to become more focused to make make coherent progress. I have a very bad habit of picking up a book, reading a bit, working out a few details, and then moving on to other random topics in other random books. In doing this, I don't really feel like I accomplish much. 

To rectify this admittedly undisciplined approach, I have decided to select core source material from each of the three major areas listed above and focus on it until I have assimilated all the information in that material. For analysis, I have selected Amann and Eschers' Analysis, volumes I, II, and III. I made this choice because out of the analysis texts I have surveyed, theirs seems to be the most comprehensive and treats elementary and advanced analysis as a unified discipline. 

My basic strategy is to treat each theorem, example, etc. as a problem and give a fair amount of effort to proving before consulting the text. I think this is probably the best way to approach the material for maximum understanding but it requires a considerable amount of time. There are probably thousands of these sorts of "problems" among the three volumes. Ulitimately, I would like to end up with a notebook (which would probably number in the thousands of pages) that contains all of the details to all of the theorems completely worked out, as much as possible, with my own thoughts. Again, this seems like it will take forever and my time on this earth is unfortunately finite. I'm reasonably confident though that the production of such a set of notes would lead to at least a fair level of mastery of the material in question.

Can anyone suggest an alternate strategy that might be more effective in terms of time but that would lead to a comparable level of mastery?

It is also a problem that I might actually prove a fact completely on my own but then, a month later, might not be able to recall it in a time of need. What strategies are helpful for best ingraining this material (other than the obvious "Work lots of problems" approach)? 

Would appreciate any tips or pointers.

This was supposed to be a comment, but it is too long and there may be lessons in it from what I've experienced.



This is a great question (I would add a bounty from my own rep if this wasn't community wiki), and it is also a very personal issue that I struggle with myself. I have a similar style of study to the one you described when it comes to things I am really interested in, rather than things that happen to be part of the syllabus on an undergraduate/graduate course I am taking (those subjects falling into the latter category tend to all get the same treatment from me -- go to the lecture, absorb the main ideas, briefly look at my notes later to see they make sense, then ignore it until I need it for some problem set or an examination).

However, I find that your style of study (call it the hard grift method) means that I am often a little behind classes or lectures, despite the fact that I am trying to pursue a deeper understanding of the material I enjoy. Unfortunately, the style of exam questions means that this level of understanding rarely helps. One can ask oneself whether it is worth the trouble, and ultimately the answer to that question depends on what you want to get out of your learning.*

I am keenly aware of the approach of what Stefan Walter above calls the 'superficial' mathematician, which I do not see as at all disparaging (and for the record, I do not think he does either). I do not really believe in innate talent, but there are many mathematicians smarter than I who seem to pick up just as much knowledge as I might from the hard grift method, by instead coasting from an article to a textbook, to a set of exercises, to a pre-print, while making minimal notes and seemingly picking up the salient points naturally, and then having a fruitful discussion with others about their new findings almost immediately (call this the flowing method). From what I read of Terence Tao's blog this is the natural progression from an undergraduate mathematician to a so-called 'post-rigorous' mathematician.

The flowing method seems to reap more benefits, but it also doesn't seem to be a ticket you can buy. I have a few friends already on their PhDs (I am about to finish my humble MMath) and, without wanting to make this sound like a cop-out, their brains seem to work in a different way to mine. It may very well be the case that I am yet to make the transition because I have not yet put in the hours, but I believe that 'putting in the hours' boils down to passion. If you aren't passionate about what you are studying, you won't put in effective hours, and you won't make the transition to post-rigour.

(Aside: I would like to think that one day I might make that transition, but as it stands, I am not sure the life of a professional mathematician is for me!)



*To answer your question succinctly: you need to find out what it is you want out of your learning. If it is pure mastery, an effective method for you to try might be: stick to hard grift for a little while, but if you find you've reached a level where your intuition is guiding you more than rigour is, then stop and evaluate, and consider taking your learning to a higher level where the details of proofs are not the most important thing any more. In particular, re-read Terry Tao's post in the above link.

If, however, you enjoy learning for its own sake and want to pursue personal understanding (which I think the hard grift method is best suited for) then you should always keep this goal in mind. Personal understanding is more gratifying than pure mastery; it should be the goal of any true autodidact (see the last section of this great article by William Thurston).
