> I graduated with a Comp.Sci bachelor with a similar GPA. Spent around 10 years as a programmer in the industry and came back to get into the masters program. I was almost laughed off (a good thing) stating I would have to do another bachelor.

Can you expand on this? I'm similar right now. Want to go back and get my masters. Graduated in CS about 12 years ago. Mid 30's. What do you mean about having to do another bachelor? I have not heard this before.

> Sold my house, got rid of all my stuff and enrolled in pure math bachelor's. Best decision of my life.

I recently just bought a condo downtown. One because I never plan to move again and rent goes up at least 3-5%/year and two because I can easily rent it out if I do end up leaving. The University of Minnesota is only a mile away from me at the moment. Mortgage is probably a little high for a grad student/TA salary considering I'm making well in to the 6 digits right now. This is my only debt and all my stuff is not much. Mostly things I can't really sell for much now or are required to work and live (computer, desk, monitor, clothes, eat, sleep). I have a couch and a TV to relax outside of work.

My GPA was 2.37 and I would've had to take so many classes to increase my GPA up to the cut off point of 2.7 (B-). With 90 credits worth of classes, you'd need 90 credits at 3.0 (B average) to make up for the difference, or less if you get better grades and that means you're on the low end of what they accept.

Now I presume if you did 2-3 semester with a B+/A- GPA, they would take that as testifying you can handle the masters and let you in, however I'm enjoying math way too much right now and there are several classes (Algebra 1-3, Topology, Differential Equations and several classes in statistics I intend to pick in the option block) that will come in handy if I head into ML masters I'm also interested in Type Theory and all of Discrete Mathematics. Also, I feel math is a great program to improve at general problem-solving.

The first semester was really challenging, some classes I had in fact already done (Calculus 1 and Linear Algebra) turned out to be surprisingly difficult. I'd say around halfway through the second semester I felt I had gotten my younger brain back.

I don't have expensive habits, have two restaurants meal a week, own a car and live at the university residences (rent is 390$/month, parking 850/year). My cost of life seems to be around 12k CAD/year and am Canadian (tuition costs are 1600/semester) so I really have no idea how much you'd have to have saved up if you are in the USA.

My GPA 12 years ago when I finished was 3.5 I think. There about anyway. I figured you were referring more to the length of time you were out of school, not your GPA.

My mortgage is far north of $390, haha. I don't have or need a car though. I lease out my parking spot for $150/month or more. If I go and get accepted I'll have either work pay or try and see about scholarship or something. My brother and best friend got free rides through their master and Phd.

You don't need to pursue a second undergraduate degree if you just need to fulfill certain courses for graduate admissions.

Check out: https://ccaps.umn.edu/non-degreeguest-students

See if other schools of interest have similar programs if that one isn't a good fit.

See if you can take courses for credit/get research experience. Then apply for your desired graduate programs.

This is a good way to get letters of recommendations from professors too.

Well done!

Jeff, I'd be curious to know. Going through TAOCP is on my lifetime-to-do and feel I am getting close to tackling it again however I have no time right now. There's also so many other things I want to go over (some higher order logic, TAPL, PFPL, the Software Foundations books, compiler design and probably won't pass up some category theory being abstract algebra seems accessible to me).

Do you feel TAOCP is worth the time investment or should I just forget about it and tackle something like your book and spend the rest of my time on other topics?

I'm not sure I can answer that question for anyone but myself. I've worked through quite a few pieces of TAOCP when I've needed to understand a particular topic, but I always find that I lose interest.

But then I've never been able to learn anything by just reading. I always have to have a target problem in front of me, and then I'll read (and get frustrated by) every book ever written to figure out the best way to think about that problem. (Which means I've read a few dozen pages from hundreds of books, and I have pretty huge gaps in my math background -- abstract algebra and category theory being two big examples.)

For some target problems, TOACP has been incredibly helpful, but for most of them it really hasn't. Knuth and I just care about different things.

For the same reason, I can't recommend that anyone work through EVERY problem in my book, either. Find the parts that are interesting and/or useful to you, and work on those. If you get tired or frustrated, work on something else; maybe you'll discover another reason to pick up my book again later. Or not.

Climbing the mountain is much more rewarding than studying the trail map.

As you've already got an answer from Jeff, I thought it might not hurt to add an additional one. IMO, you should ask yourself why you want to read TAOCP; doing it just because everyone recommends it is probably not worthwhile. Read it if you find the material or presentation interesting.

IMO one can think of each chapter (only 6 completed so far) or even each major section of TAOCP as a very deep book/monograph on that specialized topic. The writing is clear and delightful (IMO), but each of them does tend to go rather deep, more than you may care to know about that topic — so each page will require a fair bit of attention; it's not easy going. You'll get an in-depth understanding of a narrow sliver of topics.

Why not read a few of the newer sections and see if you'd like to read more in the same style? Knuth has been putting draft versions online, and they are collected here: http://www.cs.utsa.edu/~wagner/knuth/ — for example, you could read Pre-Fascicle 3B, which is on generating all [number-theoretic, or set] partitions, or Pre-Fascicle 1B, which is on a fascinating (and little-known) data structure called Binary Decision Diagrams. He uses these to solve many interesting problems, different from the focus of typical algorithms books (which would probably dismiss these methods as “brute-force”, as they don't affect the asymptotic complexity but do affect what's practical to do on real computers).

Thanks for sharing, really inspiring.