It's unbelievable that the average human being has access to the lectures of some of the best universities in the world for free. 31 hours of in-depth mathematics by some of the best people in their field.
Although I have always been struggling with keeping up with long lecture playlists. I always try to find shorter videos which explain the concept faster (although probably lacking depth). And end up ditching it halfway as well. Perhaps the real motivation to keep up with the material comes from actually enrolling the university? Has anyone completed such type of lectures by themselves? How do you stay consistent and disciplined?
I find courses in some platforms (coursera/khanacademy) a bit more motivating because they kind of push me with deadlines. I guess I am used to deadline-oriented studying.
I love math, completed a PhD, and am very self-disciplined. But even so, I don't think I would have been able to learn much on my own with video lectures, at least not at the start. For some reason, it seems like you need to reach a "critical mass" of knowledge first before you can do that, and I've observed that a crucial component is being in a program with others, and definitely having a very experienced mentor.
Without a very experienced mentor, I think it's very difficult to get to the independent-learning stage with math. That's the key. You need someone to go through your work, correct you, and make sure you don't go off in a very wrong direction.
So my advice is find at least a graduate student in math to help you. It's like a piano teacher, if you've ever taken piano, you know it's absolutely mandatory to have a teacher. People who self-learn from the start end up being able to play but not very well.
Edit: one other crucial component is time. If you're really interested in knowing something like linear algebra, analysis, or calculus with fluency, expect to spend at least 10 hours per week on it for a year. Two hours per week will give you a cursory and very weak understanding only.
t8q8 1 hours ago [-]
I completed an earlier version of this class and found structure to be helpful. Found consistent time and place each day to spend some time learning and that helped a ton, but still had weeks of not touching it so the struggle is real :)
A bit of a side note but I find that the lectures are not the most interesting/useful part of those courses. The problem sets and the time spent trying to solve them ended up solidifying so many ideas that I had fooled myself into believing I understood. So I highly recommend heads-down solving some problems. It sinks much more time than the lectures but you come out of it better off
onetimeuser24 2 hours ago [-]
I got through a few lectures by recognizing that I didn’t have the mathematical training/practice to finish up one video in one sitting. Often times I would need to scurry on over to have some basics explained to me on another site. I did one lecture over several days (weeks if I had to). I think most of the discipline comes from expectation management. Expect to get stuck and need a few moments or days or weeks to mull something over until it becomes more intuitive. Keep a list of things you do and don’t understand (a simple text file / paper is enough) and keep doing it for a few months if you have to and you’ll get there.
globalnode 2 hours ago [-]
Its so hard to be self disciplined like that, I find I have to enroll to force myself to engage. I know its a weakness.
William_BB 2 hours ago [-]
In my experience, coursera/khan academy courses have never been able to compete with a rigorous university course. They're great resources when you need alternative explanations, but never stood up on their own.
I think long lecture playlist is a feature, not a bug. It's much harder to commit to such material when you're not full timing education.
barrenko 1 hours ago [-]
My 5 cents, the value of KA is that it gives you some sort of basic curriculum you can follow. To finish calculus (the "basic", single variable) I've had to pull in lots of other books, youtube channels, courses from other universities, but it still has it's worth. It's like a rope bridge over a high river.
Major weaknesses are some cool sections like Linear Algebra that have no exercises in their respective "tree", but that's very rare.
rhubarbtree 2 hours ago [-]
“A world class education available for free, to the undistractable.”
There are a few unusual parts, like the last lecture ("Large Deviations"). I'm not familiar with the entire course, but IMO the lecture on state machines is very good; it discusses invariants and uses an approchable example (the 15-puzzle).
If you have never looked at it, the problems there are very nice. For example, instead of some dry boolean logic problem about A and Not(B), you have Problem 3.17 on page 81, which begins:
This problem examines whether the following specifications are satisfiable:
1. If the file system is not locked, then. . .
(a) new messages will be queued.
(b) new messages will be sent to the messages buffer.
(c) the system is functioning normally, and conversely, if the system is
functioning normally, then the file system is not locked.
[...]
(a) Begin by translating the five specifications into propositional
formulas using the four propositional variables [...]
mturmon 3 hours ago [-]
I was also pleased to see large deviations, although the lecture notes don’t actually define what a large deviation is.
They do give an example of a Chernoff (exponential) bound for a sum of iid random variables. The bound of course has an exponential form - they just don’t call it a large deviation. So it’s a bit of a missed opportunity, oven that the name is in the chapter title.
These bounds come up all over the place in CS, but especially lately in learning theory.
3 hours ago [-]
cubefox 21 minutes ago [-]
A lot of these topics sound interesting, though I think the average software engineer needs approximately none of that. When I first started programming, I was surprised how little mathematics was involved in practice.
Of course, these MIT lectures are aimed at computer scientists, not software engineers, which US universities consider to be quite different.
Although I have always been struggling with keeping up with long lecture playlists. I always try to find shorter videos which explain the concept faster (although probably lacking depth). And end up ditching it halfway as well. Perhaps the real motivation to keep up with the material comes from actually enrolling the university? Has anyone completed such type of lectures by themselves? How do you stay consistent and disciplined?
I find courses in some platforms (coursera/khanacademy) a bit more motivating because they kind of push me with deadlines. I guess I am used to deadline-oriented studying.
If anyone else is struggling with attention span and is looking for shorter lectures (although they may not have the same depth): https://www.youtube.com/@ProfessorDaveExplains/playlists
Without a very experienced mentor, I think it's very difficult to get to the independent-learning stage with math. That's the key. You need someone to go through your work, correct you, and make sure you don't go off in a very wrong direction.
So my advice is find at least a graduate student in math to help you. It's like a piano teacher, if you've ever taken piano, you know it's absolutely mandatory to have a teacher. People who self-learn from the start end up being able to play but not very well.
Edit: one other crucial component is time. If you're really interested in knowing something like linear algebra, analysis, or calculus with fluency, expect to spend at least 10 hours per week on it for a year. Two hours per week will give you a cursory and very weak understanding only.
A bit of a side note but I find that the lectures are not the most interesting/useful part of those courses. The problem sets and the time spent trying to solve them ended up solidifying so many ideas that I had fooled myself into believing I understood. So I highly recommend heads-down solving some problems. It sinks much more time than the lectures but you come out of it better off
I think long lecture playlist is a feature, not a bug. It's much harder to commit to such material when you're not full timing education.
Major weaknesses are some cool sections like Linear Algebra that have no exercises in their respective "tree", but that's very rare.
https://ocw.mit.edu/courses/6-1200j-mathematics-for-computer...
Lecture notes:
https://ocw.mit.edu/courses/6-1200j-mathematics-for-computer...
There are a few unusual parts, like the last lecture ("Large Deviations"). I'm not familiar with the entire course, but IMO the lecture on state machines is very good; it discusses invariants and uses an approchable example (the 15-puzzle).
Text (last revised 2018): https://courses.csail.mit.edu/6.042/spring18/mcs.pdf
If you have never looked at it, the problems there are very nice. For example, instead of some dry boolean logic problem about A and Not(B), you have Problem 3.17 on page 81, which begins:
They do give an example of a Chernoff (exponential) bound for a sum of iid random variables. The bound of course has an exponential form - they just don’t call it a large deviation. So it’s a bit of a missed opportunity, oven that the name is in the chapter title.
These bounds come up all over the place in CS, but especially lately in learning theory.
Of course, these MIT lectures are aimed at computer scientists, not software engineers, which US universities consider to be quite different.
https://ocw.mit.edu/courses/6-1200j-mathematics-for-computer...
https://www.youtube.com/playlist?list=PLUl4u3cNGP61VNvICqk2H...