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Cell Biology: Mitochondria

edX · Harvard University · 1 HN comments

HN Academy has aggregated all Hacker News stories and comments that mention edX's "Cell Biology: Mitochondria" from Harvard University.
Course Description

A human-centered approach to the fundamentals of cell biology with a focus on the power plants of the cell - mitochondria.

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This course is offered by Harvard University on the edX platform.
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All the comments and stories posted to Hacker News that reference this url.
Occasionally I see posts, for example on reddit but also discussions here, about what other programming languages a programmer could learn as the next (and higher) step in ones ongoing education.

My suggestion for what to do after the CS degree, a road I took myself during the last few years, is to go to edX (or Khan Academy for any missing basics) and at the very least take MITs "Introduction to Biology", which actually is an introduction to genetics (when you learn biology you first have to understand cells). Also, neuroscience, for which there are many courses (longest one on Coursera, "Medical Neuroscience", with an excellent teacher), from the basics (https://www.mcb80x.org/) to computational neuroscience (https://www.edx.org/course/computational-neuroscience-neuron...).

I found understanding the basics of biology a lot more informative than learning new twists about some functional programming concept. It introduces you to a massively(!) parallel world where statistics rules, and errors/outliers are actually essential to functioning biological systems. You may find that if you remove all errors, for example that a protein is made that is not supposed to be made because it's not supposed to be needed, actually is essential, because only by making it does the cell notice that a different (better) fuel option has become available (that is from a concrete example, see the linked course :-)). So definitely add plenty of statistics courses until you learn to think "big". Each time you think about a problem think about that thing happening a trillion times instead of individual cases, until this becomes a habit. This helped me a lot, because most people focus their mind on single examples, for example when making suggestions how to improve society (hint: suggestions that sure work for anyone, but if everyone tried it would quickly unravel). Okay, in the last two sentences I'm going out on a limb (claiming that learning biology and statistical thinking helped), but definitely try some biology, statistics and neuroscience guys. It's all free and most of it high quality. And the statistics knowledge is just as good for machine learning so you need that anyway.

Also recommended: "Principles of Biochemistry" (https://www.edx.org/course/principles-biochemistry-harvardx-...), although I would say you should not try to do all the exercises because it will be way too much work (and highly demotivating, looking at how the discussion forum shows how the nr. of students very quickly grows thinner from course section to section) to try to learn all that stuff by heart. Also: "Cell Biology: Mitochondria"( https://www.edx.org/course/cell-biology-mitochondria-harvard...) to understand where the power comes from.

Also check out individual universities, some have a lot of free courses (sometimes using the edX platform software, which is open source, e.g. Stanford) hat they don't put on 3rd party platforms like edX.

waiquoo
Would you mind talking about what field or area you work in?

I came from a bioengineering background and ended up doing a lot of computational work (signals and communication systems, ML, FEA), so I feel like we are arriving at the same conclusion from opposite sides.

ItsMe000001
I studied CS, worked as a consultant and at a major Linux company, later as a freelancer. Learning stuff feels good :-) Even better when it's something I never ever expected to learn, since I thought that after choosing my field of study for university my path was all set. Thanks Internet - possibilities truly have increased by orders of magnitude compared to my youth!
devgutt
IMHO these courses only scratch the surface, good to learn a thing or two, without much applicability. I am right now searching for a degree path in Biochemistry or Molecular Biology online. I want to spend time on it, but be able to actually apply my knowledge. There are so few of them (maybe because of the lab classes, idk). I've found online degrees in ASU (https://asuonline.asu.edu/online-degree-programs/undergradua...) and UF (https://ufonline.ufl.edu/degrees/undergraduate/biology), but they are really expensive. Biology is the future, but unlike the article, I think it will make software obsolete altogether.
kharak
Do you by any chance did come across an online course for biochemistry or something similiar? I've wanted now for quite some time to study biology and change my career in that direction, but no relevant degree seems to be designed for remote study.
ItsMe000001
Look at the "Principles of Biochemistry" course I linked to. Even when OP says "it's scratching the surface", that was in comparison to a complete several years study, that course by itself is extremely involved and pure biochem. It's "only" a single course, but let's wait what you say after unit 3 - because judging by the forum participation, about 99% of people who join that course won't even make it past the 2/3rd mark. So if you can stomach that one course it would be a good sign. I read that about chemistry in general, should be the same for biochem, that if you study in those fields the load is quite extreme.
ItsMe000001
> IMHO these courses only scratch the surface

Of course - that is what I recommend to programmers and CS majors, working in those jobs, on the side, not as a career path.

But in any case, those are "real" courses, so "scratching the surface" not because they are dumbed down but because those are the freshman courses. Of course year 2+ students will get more advanced courses not usually found on edX (although they have quite advanced topics in physics, for example https://www.edx.org/course/mastering-quantum-mechanics-part-...).

As I said, an alternative to learning yet another only mildly different programming language (that runs on the exact same pieces of silicon as the other ones they already know, so it cannot be fundamentally different by definition).

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