Finally can see you are doing this~

Whatever it is, I believe you will ace it!

Thank you! I appreciate your input.

yes 😖

The first and most important factor for me was a spreadsheet, on which I put all the courses that I have begun, and under each course title I put _all_ the tasks I have to do, such as week 1 exercise, week 1 peer review, week 2 exercise, … along with their associated deadline. I marked each task in red when its deadline was within one week, dark red when it was due _next,_ and green+overstrike when it was completed. There was a separate section for exams, similarly structured. This allowed me to easily see where I am going and what I should do next. I would update the colors every day and after completing each exercise, and I would move the most urgent courses to the top of the page. This is how I could keep track of everything. Despite this, I occasionally forgot to do some peer reviews (by inadvertently marking it done), which concretely caused me to miss the highest course grade for Logic II and Statistics I. If you are going to cram your schedule, I definitely urge you to maintain such a spreadsheet. It was vital for me. At first I tried to follow all lectures, but eventually, I stopped attending any lectures except those that have mandatory participation or those that I was particularly interested in. If the subject was particularly difficult, I would watch&listen to the lecture VoDs in a dedicated session at the beginning of my personal weekly session of doing the exercises for that course. For Interactions and Bodies and for Statistics I, if I had realized from get-go that the VoDs were as useful as they were, I would have done it from the start and had a significantly easier time with the courses. I _never_ attended any exercise sessions (laskarit), something that most students definitely require and find invaluable. These sessions are where an instructor would be present, and students could ask for guidance on particular exercise questions. I also never did any voluntary/practice exercises; but only those that directly influence the course grade. I relied on my wits to get me through the exercises: when I didn’t understand something, I would first attempt to learn it from the course material (book/booklet/whatever), and failing that, look for lectures that teach it. Failing that, I would accept that I get zero points for the exercise and I would try to learn it from the model solutions that are posted after the exercise return deadline closes. This method is definitely not suitable for everyone. It also caused my answers to often differ significantly from the model answers, as I came up with the answer (usually correctly) by deducing it from what I already knew rather than by following the method taught at the course. Sometimes I was penalized for that, sometimes not. There was a significant factor in gambling the peer reviews. Not attending lectures definitely contributed to me getting bad grades for Algebraic Structures II, for Series, and for Linear Algebra II. This appears contradictory, because I got good grades for Algebraic Structures I and Linear Algebra I despite not attending any lectures there either. The difference was in the combination of course materials + exercises. Good exercises direct the student into studying the relevant things, and good course materials are easy to digest. Still, overall, the time cost by far outweighed the benefit of attending lectures. For most courses, I tried my best (barring the aforementioned constraints). An exception was Mathematics of Machine Learning I, which was extracurricular for me* (although I am requesting it to be included in my degree), which is why I quit doing exercises for the course mid-way through, when I had calculated that I am already guaranteed at least 3 for the grade; and for the Linear Algebra series, where I never returned extra credits exercises due to them being particularly time-consuming. *) I also began doing Mathematics of Machine Learning II, but the course was organized very differently compared to the first part, and there was mandatory attendance bullshit that caused me to drop this optional course early on. This is what the poop icon in my listing denotes on that course. There were also a few other poop-marked courses; all of those were courses or exams that I had signed up for, but cancelled for one reason or another.

The trick is not being creative in the traditional sense of creating something unique - have you heard this dudes music ? He can create music but its not up there with high level creators, his computer CGI skills are by definition creative but he is essentially making known objects and systems. You cant have a horse pulling the cart in many directions. You have to get all your horses lined up and pulling in the direction you want to go - as a consequence, you cant excel in other directions. So ? To learn. Get organised, focus and go over the material as often as is practicable.

The trick is having a very high IQ. No other trick.

@@newvocabulary hardworking and patience. IQ can be devleopped

@@newvocabulary more importantly pulling from a lifelong bank of knowledge from directly or indirectly related material helps. How does fretting over iq levels help in learning? You are already shooting yourself in the foot by believing that "innate" talent and not hardwork dictates your learning journey. I personally believe that most ppl can learn how to do most things especially if they don't have to be in the forefront of their field and engage with unprecedented problems. Just cause it took someone a few weeks and it took you a year isn't a reason to abandon your passion or to abandon your learning path.

It's not really inspiring, quite the opposite actually. Highly intelligent man succeeds where you wont. I'm happy for him, but he's a genetic anomaly that you or I simply will not ever be.

@@newvocabulary That's a bit negative view on things you have there. This kind of attitude might push you behind in the long term.. Bisqwit is a guy who set up a plan for the things he wanted to do in life and follows that plan strictly. To me he's an example of dedication and focus , not an anomaly.

@@vancedajcg8724 I work hard every single day, it's always frustrating knowing that I'll simply never be intelligent enough to grasp material as fast as others though. I still do highly technical work for a living, but sometimes my turbo-autist contemporaries absolutely baffle me with the amount of information they're able to process, store, and recall without effort. I'm happy they exist, and happy that I exist, however I can't say I live without a bit of jealousy. I'm content knowing that truth despite it's unchangeable reality.

@@newvocabulary I have a tech-leader that fits that description exactly. It feels as unfair how he's able to find out bugs in 10min that I've been stuck around 2h with no progress. And the age gap is just 1year old so i can't help but feeling as it's my fault for not being working hard enough

But to balance things out, they struggle with other aspects of life

At one point when doing peer reviews for Algebraic Structures I, one of the anonymous submissions that I received for reviewing was one where a student had accidentally submitted their exercises for Topology IA, to this course. The exercises looked so boring and difficult that it persuaded me against taking those courses… I have not actually heard of topological data analysis.

my friend you are worth more than that

I’ll be learning Linear Algebra in uni too, do you remember any videos containing Linear Algebra explanations? I’m interested in learning from those videos too.

Genius or not. His ability to focus for long periods of time appears super anomalous.

He was born 1978

he's 50? seriously???

@@levonschaftin3676 Around 40 I think. And no one is ever too old to pursue college

@@klebleonard I didn't say that, the wow was referring to his youthful look.

My favorite subtopic was optics. I also enjoyed solving the currents in a classic resistor circuit using matrix calculation.

@@Bisqwit Neat, did you do those by hand? We were allowed calculators because linear algebra was not a prerequisite.

As long as you got an equation group, the exact mathematical method of solving the equation group was irrelevant. Because our exercises were all done online (PDF files, and you submit a PDF file containing answers either as a document or a scan of photos), there was no way to control whether someone used calculators or e.g. Wolfram Alpha. Of course you still had to justify your answers.

They are _included_ in my list specifically because I am going to take them :-) Gray because they are not part of curriculum. If I didn’t, they would not be listed unless they are mandatory…

Yeah, I have one on the editing table right now, but I also have other things taking my time… Sorry about that.

World's happiest pigs in s*

Finland most happiest country? I thought that was Denmark. Finland actually has alot depression because of very little sun.

Finland has dominated that ranking for at least four years straight. Denmark has not been far behind.

@@Bisqwit i stand corrected. I have looked it up. But concidering Finland being the happiest place. Its has pretty high suicide rate among EU countries. Almost the highest. Pretty contradicting data.

Yeah, neither would I have anticipated that 15 years ago.

I used Inkscape to make it.

@@Bisqwit Thanks for sharing, much appreciated!

Let's say the truth, Bisqwit isn't an ordinary student or even a PhD for that matter! Have know and met many PhD's in CS/EE with not even half as much as Bisqwit programming skills, talent and ingenuity. and if people disagree? well here is to me! they just like titles and colored ties!

Thanks. What do you mean by "did 2 masters in each of those fields"? You got two master’s degrees?

@@Bisqwit Yes.

I hope you enjoyed it!

@@Bisqwit Partly, unfortunately. Please excuse this rant. Mathematics got more fun in master because stuffs from bachelor started to get properly used and everything started to make more and more sense. Morever the people in the math faculty were just "better": When i did good things, i would get rewarded and they would be proud for me. Not only that mathematicians are more direct and honest. They are not so sociable but when you talk to one, you get the answer you expect without noise. In mechanical engineering it was the opposite. In almost every subject i managed to beat the prof at their own game and everytime, they would hate me and fight just to be right. In math, my profs would apologize when they made mistakes. In mechanical engineering, they will justify them. Not just the profs, the students are like this and this made projects harder. Mechanical engineers are not very intelligent. The study doesn't teach how to find solutions, but how to use preexisting ones, so that when something seems the least out of place, they will assume that the problem is unsolvable. They also have such big egos, people thinking they know everything and blame you for knowing more than them. Many would say: "we are not all mathematicians with mega programming experience". I had the chance to work in the mechanical engineering faculty for a while and it was the same problem. Imagine having a teamlead jealous of you. To whom, everything you say is wrong and everything he says is right. I worked with electrical engineers, informaticians, mathematicians, physicists but mechanical engineers are just the worst. I studied master mechanical engineering mostly because i was curious, but a lot of the subjects were just grind-work that are useless. Honestly, if i knew how mechanical engineering (master) was going to be, i would not have started it. Mathematic is just better and should have been enough.

That sounds awful. I am sorry that you had to experience it. Thank you for sharing your story. There are indeed cultural differences between disciplines.

In general, universities of applied sciences operate quite differently. My experience is from the late 1990s so I don’t know how it is nowadays, aside from glancing a study schedule from early 2000s, which left me unimpressed. If I had known in late 1990s how universities operate, I would have applied back then. My biggest frustration with _any_ studying was rigid scheduling and studies that had nothing to do with the topic.

Electromagnetism was actually quite heavy on integral calculus. For example, the Biot-Savart law: B⃗ = µ₀/4π ∮(Idl⃗ × ʳ⃗ / r²) or this screenshot from the model answer to one of the exercises: i.imgur.com/VkT220L.png Likewise for Radiation fields & Photons: i.imgur.com/p70Q8tG.png with a touch of some differentials too.

How he did it so quickly? Dense neuro axonal structures and long dendrites, ie very high IQ thanks to winning the genetic lottery in that department. It takes a fairly high IQ to even do it in a regular time frame, an average IQ person simply can not do it at all. Once you learn about genetics you will understand that no one should be praised/judged for their accomplishments/failures since it's just a natural course of events for them. Understanding breeds motivation, it's a self bootstrapping process - you observe a concept -> if you understand it -> you become motivated to further observe the next one -> you grasp more -> motivated -> grasp -> motivated -> etc. If you can't grasp or grasp too slow you're not motivated to invest further effort

@@Ljosi going further, free will doesn't exist

@@maybenot7298 what does that mean?

@@amir3515 ofcourse free will doesn't exist, the universe is deterministic. At every time interval the current state is derived from the previous one. Given a hypothetical supercomputer of adequate computational power available at the moment of the big bang - every subsequent position/state of every particle could have been known upfront

@@Ljosi interesting that it exists though and we feel like we have free will

Huh, I held some free days, but sometimes I would literally be working round the clock on some exercises. Other exercises might take just a few hours. I had a weekly schedule in each period; I kept track of when is the deadline of a particular thing I had to. For example, Tuesday for linear algebra and statistics, Friday for logic, Saturday and Sunday for physics.

One topic within robotics is inverse kinematics. I find it very difficult. I don’t know if there is a course that can make it palatable.

@@Bisqwit brother having seen u do amazing projects over the years, I dont think it would be too hard for ya to get running with :) regardless, even I was thinking about ways to avoid the "nasty" parts of this, and basically made my mind up last night that I want to work with virtual robots... in simulators, getting them to do something xd that would be more realistic for summer xd

_Most_ courses had some selection of these ingredients (very few had _all_ of these): - Pre-made video lectures, usually short, that you could watch at any time of your choosing (VoD), including using fastforward; each video focuses on particular topic - Live lectures, held in Zoom, where you could ask the lecturer for information, and the lecturer might use tools like Presemo to poll the class; the lecture would be recorded and available as a VoD afterwards (of course without audience participation) - Exercises, usually calculation heavy, presented as PDF file online, and you have to return your answers as a PDF file (either saved from a word processing program or a collection of photos/scans) - Peer review: You grade your own exercises and also anonymously two other person’s anonymous exercises. You get extra points for doing so. The points for your own exercise will be an average of your own + peer reviews, unless they diverge too much; in that case, a course assistant grades it and the three reviewers will receive fewer peer review points. ­- Online exercises (”STACK”), on Moodle; these are either multi-choice, or questions where you have to fill in a value or a formula. They are automatically graded. Sometimes you can retry infinitely many times, sometimes retry count is limited, sometimes getting it wrong adds penalty so on the 2nd attempt you get fewer points for getting right. - A self review, where you review your own learning and give a grade to yourself with good written justifications. - A course exam, held online. This works identically to either the PDF exercises or STACK exercises, but there will not be peer review; only assistants (or automatic in case of STACK) grading. The course grade is assigned using a weighted sum of these; weights vary. A typical way is ⅓ exercises+reviews and ⅔ course exam.

and the educational system in finland is the best. He told he progammed in C with 15. At age 15 we did nothing with computers at school. (ok personally I programmed a little in BASIC) Later in 12th grade we started in Pascal with things like calculationg Resistors, simple 3 lines of code.Education in germany regarding IT and digital logic, its hillarious. Companies beg for foreign workfoce...

The education system did absolutely _nothing_ to teach me C, or C++. That was all me. What it did was teach me BASIC and Pascal when I was 14 and 15 respectively. But it did teach us how to use DOS command prompt. Which, mind you, was considered _vital_ back in 1990s, so that is good. Not so much in this millennium.

The course Scientific Computing I, which you noticed, covers the following topics: - Basics of programming in Python - Basics of Jupyter Notebook (interactive frontend to Python) - Basic commandline commands in Linux - Basic concepts and methods of statistics, such as least squares fitting - Elementary knowledge on using databases to find scientific knowledge - Foundations of creating scientific documents. I think I’ve got all that covered. Part two, Scientific Computing II (also a physics course), covers the following: - Most important aspects of Fortran for scientific computing - Writing moderate size programs in Fortran - Compiling a program from its source code - Experienced in using Linux as a programming environment. I think I’ve got all that covered too, although instead of Fortran I would use C or C++. Then there is a separate 10 ECTS course “Numerical Methods in Scientific Computing” which belongs to the master’s programme in materials research. This covers the most common numerical methods and algorithms, and their strengths and weaknesses, and their use in self-made programs as well as the numerical libraries and programs. The detailed list is: - Tools, computing environment in Kumpula, visualization - Basics of numerics: floating point numbers, error sources - Linear algebra: equations, decompositions, eigenvalue problems - Nonlinear equations: bisection, secant, Newton - Interpolation: polynomes, splines, Bezier curves - Numerical integration: trapeziodal, Romberg, Gauss - Function minimization: Newton, conjugate gradient, stochastic methods - Generation of random numbers: linear congruential, shift register, non-uniform random numbers - Statistical description of data: probability distributions, comparison of data sets - Modeling of data: linear and nonlinear fitting - Fourier and wavelet transformations: fast Fourier transform, discreet wavelet transform, applications - Differential equations: ordinary and partial differential equations This sounds more like what you described. But it still is not part of any curriculum that I have. I don’t even know what subject could I theoretically group it under.

@@Bisqwit I suspected that the course would also cover introductory aspects that you would obviously already know. Back when I was an undergraduate (and not in Finland actually), the initial focus was more on the numerical aspects (how to solve a problem numerically on a computer, and how it could actually turn wrong) and less on the coding. Fortran and C came only in master years for the numerical methods but we could skip it if we already know about it (and get advanced coding lessons). The master programs seems actually more into what I had in mind. Topics like differential equations, Fourier transform, Linear Algebra algorithms or interpolation are actually very useful in physics and maths, and the subtleties on what is under the hood are often overlooked by students. Considering the subject, well, I would put it under the umbrella "scientific computing"... which is general but quite vague, I admit. ^^ But anyway, I just saw the grey box with my favorite discipline on it and couldn't help but rant a bit. I am pretty sure that if you get interested, this would be something you would catch up with without problem. The most important thing is that you make your own courses selection and take them at your own (apparently pretty fast) pace.

Update: I did actually complete Scientific Computing I & II this semester. I got 100% points from both courses.

I don’t actually know. Well, I do know that the _master’s_ thesis does require supervision from a professor. I presume thus that it also requires approval of the topic. The bachelor’s thesis probably does not have such requirements. I will soon find out, as my work on that will begin in September.

Yes, I use kdenlive.

Of course he will Finnish! (sorry...)

Huh. Well, I don’t usually write shopping lists, but I do write lists sometimes in Joe. If I had to take it with me to the store, I would write it in Colornote instead.

I translated them. Why? Whim.

kzfaq.info/get/bejne/Y7d-fLumxJeWmaM.html Here is the video I quoted. This was the (sort of) celebratory event, albeit sad, for the demolition of the school.

@@Bisqwit hmm, why would the demolition be celebrated Kids will loose their school and people that worked hard to build this would be sad to see their work demolished

I thought the celebration was weird too as it was a sad event, but I was glad it was organized anyway: It was cathartic to be allowed to walk through _all_ areas inside the school, including areas that were always off-limits to pupils such as the kitchen or the janitor’s warehouse, and to revisit one last time all the places in the school that shaped and defined most of my childhood so long ago, even though some of it had changed slightly during the decades. When they demolished the school, they built a new one, a bigger and more modern one over the same lot.

I didn’t have one until like a month ago.

What’s your problem?

@@Bisqwit i'm against education systems where memorization is the only solution, no practice, just theory

Well, that’s not university you are talking about then.

@@Bisqwit I used to go to one and while we did some labs they were superficial

Well, I can attest that my preferred method of learning is to gain understanding on how things work, and I am very weak at learning by memorization. The results presented in this video, combined with the information from this post, should provide you evidence on how studies at a university actually work, at least where I come from.

Oh no, that’s a friend of mine, who was about 65 years old when that video was recorded, in 2013 (when I was 35). Not a “someone special” in that sense.