I went with a pretty high expectancy [1,2] to pursue a Master’s degree in Computer Science at one of Germany’s best Universities in Computer Science. Soon I found that the education wasn’t at all as good as I had expected. The main reasons are unnecessary complexity or pretended knowledge and academic arrogance. I will briefly explain some of these points here without going into much detail.
As you may have heard, German education prices itself by an inherent theoretical complexity. Initially, I was amazed by that apparently great and deep understanding the classroom material and professors brought to us. That was until I started to peek through the facade little by little.
First, if the Universities were really superior, why then is there so little research output compared to US Universities? It seems like the professors always had to get back and name a few things like “we contributed to Siri’s (predecessor’s) AI and MP3 was invented at the Max Planck Institute.” Come on guys those things are fossils, is there really nothing new and more tangible? US Universities like Stanford are constantly spitting out tons of successful startups and innovations . If you are German and want to know how far behind German Universities are compared to US Universities in research output and innovation in general, read this book.
Often people confuse pretended knowledge with real knowledge. Pretended or apparent knowledge is a type of memorized knowledge. The individual who displays this type of knowledge may talk extensively about a subject without truly having an understanding of it. A perfect example of this is the apocryphal story about Max Planck and his chauffeur described here. Charlie Munger explains it like this:
I frequently tell the apocryphal story about how Max Planck, after he won the Nobel Prize, went around Germany giving the same standard lecture on the new quantum mechanics.
Over time, his chauffeur memorized the lecture and said, “Would you mind, Professor Planck, because it’s so boring to stay in our routine, if I gave the lecture in Munich and you just sat in front wearing my chauffeur’s hat?” Planck said, “Why not?” And the chauffeur got up and gave this long lecture on quantum mechanics. After which a physics professor stood up and asked a perfectly ghastly question. The speaker said, “Well I’m surprised that in an advanced city like Munich I get such an elementary question. I’m going to ask my chauffeur to reply.”
In this world we have two kinds of knowledge. One is Planck knowledge, the people who really know. They’ve paid the dues, they have the aptitude. And then we’ve got chauffeur knowledge. They’ve learned the talk. They may have a big head of hair, they may have fine temper in the voice, they’ll make a hell of an impression.
My opinion is that the German education system lacks so far behind without realizing it because if you are there, you truly feel that you are getting an incredibly advanced education. Most classes consist of power point presentations which consist of 90% abstract mathematical formulas and symbols. You feel like a little alien looking down at the rest of humanity, but guess what, complexity is not equal to knowledge.
Context and true understanding are lacking. I noticed this when the professors weren’t able to give simpler answers to questions. They simply responded framing the same thing they just said before a little different. As Mortimer Adler already said it.
“The person who says he knows what he thinks but cannot express it usually does not know what he thinks.”
Ther is a good method to check for real knowledge, it is called the Feynman technique, and it goes like this:
Explain what you’ve just learned or explained, without using the words or complex concepts you just used. You have to be able to completely rephrase the concept in your own language. For example, if you are explaining energy, you can’t use the word energy. Watch this video for a little demo.
In one occasion the professor of the AI class — one of the classes for which that particular University is famous for — noticed an error on the slides which he inherited as he admitted, from the university where he studied. That was more than a decade ago! If an error can persist on a slide for that amount of time despite being looked at by hundreds of students every year, I suspect that most students aren’t really comprehending what they are looking at. Something which should cause serious concern. By the way, why are slides simply re-used through such a long amount of time? That sounds suspiciously like apparent and outdated knowledge to me.
Oh and talking about reused slides, another course for which the university was supposedly highly prized is the security course. I must admit it was pretty good. It just bothered me when I copy-pasted sentences from the slides to Google and found that all slides, without exception, were literally word-for-word copies of slides from US universities. The only thing that changed was the University Logo and the respective background colors of the slides.
But what really shocked me was the Machine Learning class.
Complexity is fine as long as it is useful. Complexity for complexity’s sake is bad.
During the whole first Machine Learning class, there was quasi-zero student participation. The professor kept talking about abstract statistics. Here a peek at the slides:
Looks all nice but where exactly are we getting with the math in Machine Learning? How does the math relate to the real world? Do students really remember every aspect of very specific statistics supposing they have gone deeply into them at some point? Maybe the reason why there was so little participation is that most students don’t know what the heck the professor is talking about?
Compare that mental diarrhea with the first Machine Learning Class of Stanford University, and you will know what I mean by unnecessary complexity, apparent knowledge, lack of context, and just bad education, and how it compares with the elegant, succinct and easily understandable explanations of Andrew NG.
A side effect of the things explained above is that people in such an environment trap themselves because they think they have superior knowledge. They fail to see that abstract knowledge (supposing that it is real knowledge) is useless unless applied somehow in the real world either through technological innovations or teaching through true understanding.
Once the press of the University wrote an article about me on a local student magazine phrasing something like this “he left US Universities in the shadows and instead came to our wonderful….” you get the idea. My initial enthusiasm met reality soon after.
Since I’ve tasted top education through online courses from Stanford and similar Universities, I simply can’t tolerate bad education. I opted for self-education through the world’s best books (here a reading list) and online courses. If I can give you one advice, don’t fall into a trap just for a University title. Just because education is free in a country, doesn’t mean it will be the best way for you to learn. Job titles don’t help a lot these days. If you feel you learn at the fastest possible rate at your current institution, by all means, stay there. But don’t fool yourself into thinking that you are learning when in reality you could do much better by self-education or by joining other Universities with a much more advanced education methodology and with the industry’s top talents as professors.
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