
Ask HN: Recommend me a course on Coursera - Eugeleo
My university just provided us with free Coursera accounts until the end of summer. However, there&#x27;s so many courses to choose from that I don&#x27;t know where to start! Please recommend me a course that you liked, preferably from the following areas:<p>- UX design<p>- bioinformatics<p>- statistics for data science<p>- mathematical analysis<p>- algebra or category theory<p>But of course, you don&#x27;t need to stick to those categories, I&#x27;d love to learn about anything new!
======
betamaxthetape
Build a Modern Computer from First Principles: From Nand to Tetris (Project-
Centered Course) [https://www.coursera.org/learn/build-a-
computer](https://www.coursera.org/learn/build-a-computer)

and then part 2:
[https://www.coursera.org/learn/nand2tetris2](https://www.coursera.org/learn/nand2tetris2)

[Both courses are free]

These are fantastic courses, by far the best MOOCs I have ever taken. I went
into them knowing nothing about computer architecture, and by the end of the
first course I was able to design a fully-working digital computer in Logisim.

While other courses consist of lectures + text content, with Nand2Tetris the
course is _practical_. The authors have developed a complete software system
to allow you to complete the course:

* A simplified hardware programming language to design the ALU, CPU, clock, RAM, etc..

* A hardware simulator and debugger to allow you to test the hardware that you develop

* An assembler for the assembly programs you write for the computer

* A compiler for the higher-level programs you write for the computer

I'm probably banging-on about this course more than I reasonably should, but
that's just because I enjoyed the course so much!

~~~
hawkjo
I have to also mention nandgame.com here. Similar idea, but all presented as
an interactive, browser-based game. Start with nand gates and build up to a
functioning computer. You never get to tetris, but it's great and super easy
to start playing/learning. Delightful.

~~~
polycaster
[http://nandgame.com/](http://nandgame.com/) You‘re welcome.

~~~
credit_guy
Oh man, a big Thank You. I kind of know where I'll be spending 10-12 hours in
the next few days.

------
dhawalhs
Here is a list of all Coursera courses sorted by ratings:
[https://www.classcentral.com/provider/coursera?sort=rating-u...](https://www.classcentral.com/provider/coursera?sort=rating-
up)

You can also filter by subjects i.e Computer Science, Data Science.
Humanities, Mathematics, etc.

Disclaimer: I am the founder.

~~~
Ao7bei3s
Is there a plan to get more advanced courses?

I'm asking because there seems to be an extreme bias towards beginners
courses, or content that is rather limited in breadth _and_ depth compared to
what a university might teach during a full masters degree.

ie, there's about 50 security intro courses (with lots of overlap of course),
one "advanced" course that's been delayed for long and isn't all that advanced
(Crypto II from Stanford), but nothing that even comes close to the various
full-semester courses covering particular niches that I took in university
(for example, we did one full semester course on _each_ of: symmetric crypto,
asymmetric crypto, side channels, "special topics" (random stuff), a
cryptoanalysis lab, and 3 more niche things - and those are just the pure
crypto courses, and even/especially within that area I feel I've barely
scratched the surface).

These university courses cover not only more topics than Coursera covers
(overall; there are many things even in this niche that Coursera has that we
weren't taught, which is neat), but within each we went into considerable
depth. In particular we tended to approach them from a rigorous mathematical
perspective (number theory, linear algebra, statistics, proofs, etc). My worry
here is that Coursera might be more geared towards people that don't need to
learn the topics well enough to be actually able to use them professionally,
let alone academically. ie, more like edutainment than education (no offense
intended. I wasn't sure if I should include that sentence cause it might sound
harsh, but I think it illustrates what I'm getting at).

We also didn't have courses that are blatant advertisements (#18568).

I don't want to put Coursera down (quite the opposite), I am genuinely
interested in your answer - Is it just me not seeing everything available? Is
the field I'm (slightly) knowledgeable about an outlier? Or am I missing the
point of Coursera (maybe it's more focused on training industry professionals
than academics than universities?) Or is it correct, and if so, is it
intentional or unintentional? Is there a single field of study where Coursera
could replace a university partly/largely/mostly/entirely? Will there be?

~~~
reilly3000
There should be less ratings of advanced materials, and there should be less
coursework. Advanced study is the long tail of learning.

~~~
harperlee
That should not affect the rating by much with an appropriate sorting. See:
[https://www.evanmiller.org/how-not-to-sort-by-average-
rating...](https://www.evanmiller.org/how-not-to-sort-by-average-rating.html)

~~~
bjterry
I would expect people who take advanced courses to rate systematically
differently from people who take beginner courses. For comparisons between
similar courses it's probably fine, but would be hard to use the scores to
compare the value of beginner courses to advanced courses.

Of course, even the definition of better here is so ill-defined it probably is
of no practical significance.

------
elliekelly
The Science of Wellbeing[1] taught by Yale’s Dr. Laurie Santos lives up to the
hype. It’s been discussed on HN a few times[2] which is how I stumbled upon
it.

If you don’t mind my asking, did your school give you access to coursera to
earn credit while the campus is shut down? Or is it just something interesting
and fun for students who might be inclined to learn something new while
they’re stuck at home? Either way, props to your school! And enjoy whatever
classes you decide to take!

[1] [https://www.coursera.org/learn/the-science-of-well-
being](https://www.coursera.org/learn/the-science-of-well-being)

[2]
[https://hn.algolia.com/?dateRange=all&page=0&prefix=false&qu...](https://hn.algolia.com/?dateRange=all&page=0&prefix=false&query=science%20of%20wellbeing&sort=byPopularity&type=story)

~~~
Eugeleo
Thanks for the recommendation, sounds great!

As mentioned above, I think the credit is due to Coursera more than my
university; either way, at least they've let me know that something like this
is possible.

It's just for fun; most of our courses are now taught over Zoom or similar
services, assignments are handled digitally and if it wasn't for the low-
quality webcams, you'd almost forget something is out of the ordinary.

------
bhaprayan
I enjoyed taking Model Thinking: [https://www.coursera.org/learn/model-
thinking](https://www.coursera.org/learn/model-thinking)

It's designed to be a foundation course for subsequent social science classes,
but I personally found the exposure to models from different fields of study
to be quite insightful.

If you're interested, there's also a book by the professor on the same topic:
[https://www.goodreads.com/en/book/show/39088592-the-model-
th...](https://www.goodreads.com/en/book/show/39088592-the-model-thinker)

~~~
pmohun
Model Thinking is the best Coursera course that I've taken. The lessons have
practically applied to many areas of my personal and professional life in a
way that far exceeded my expectations.

Scott is one of the best teachers on the topic, and makes complex models
simple and intuitive to understand.

It is a long course, but well worth it. Cannot recommend it enough.

------
randomstring
I recommend the meta-cognition course: Learning how to Learn.

[https://www.coursera.org/learn/learning-how-to-
learn](https://www.coursera.org/learn/learning-how-to-learn)

The primary instructor, Dr. Barbara Oakley, wrote the book, _A Mind for
Numbers: How to Excel at Math and Science (Even If You Flunked Algebra)_ that
isn't just about learning math.

~~~
xtagon
I second this, and if you're not sure where to start then this is a great one
because it will give you some study tools to use on your next course(s)!

------
accidentalrebel
I recommend an audiobook course from Audible called

The Philosophers Toolkit: How to be the most rational person in any room by
The Great Courses [https://www.audible.com/pd/The-Philosophers-Toolkit-How-
to-B...](https://www.audible.com/pd/The-Philosophers-Toolkit-How-to-Be-the-
Most-Rational-Person-in-Any-Room-Audiobook/1629976822)

It teaches you mental models on how to think and find a solution to a problem.
It explains the concepts behind each model quite well.

Topics include how to determine a valid argument, an iron clad argument, using
heuristics to solve problems, among other things.

My only gripe with the course I linked is that it is an audio version of what
seems to be a video version on the Great Courses website. You might want to
check that out too.

~~~
TotempaaltJ
Great Courses video version: [https://www.thegreatcourses.com/courses/the-
philosopher-s-to...](https://www.thegreatcourses.com/courses/the-philosopher-
s-toolkit-how-to-be-the-most-rational-person-in-any-room.html)

------
djhaskin987
The cryptography course taught at Stanford I have found to be excellent. it
really helped me gain an understanding of what I MAC's were, cbc encryption,
common problems with encryption schemes, etc. after taking the course I was
able to find a bug in our company's software that they didn't know about or
that they didn't know was a bug.

~~~
raegis
I agree--I very strongly recommend this course. I binged Dan Boneh's lectures
on a late Friday night like I was watching Netflix. I'm serious.

~~~
person_of_color
Did you actually complete all assignments?

~~~
raegis
No, why?

------
ajot
Experimentation for Improvement [0], taught by Kevin Dunn [1][2]. It's not
very difficult to follow, and teaches some basics of experiment design. It's
explained in a very well suited manner for non-academics, with examples about
how you can implement this kind of experiments to improve things at home or at
work.

[0]
[https://www.coursera.org/learn/experimentation](https://www.coursera.org/learn/experimentation)
[1] [https://learnche.org/](https://learnche.org/) [2]
[https://github.com/kgdunn](https://github.com/kgdunn)

------
airstrike
[https://www.coursera.org/learn/machine-
learning](https://www.coursera.org/learn/machine-learning) with Andrew Ng

~~~
silverdrake11
I would recommend Andrew Ng's updated course on Deep Learning with python
instead. [https://www.coursera.org/specializations/deep-
learning](https://www.coursera.org/specializations/deep-learning)

~~~
tasubotadas
Yeah - the updated version is much better (I've completed both of them) just
because you don't need to struggle with Matlab.

Overall, this course is extremely good mostly because Ng covers the essential
theoretical topics and gives some practical advice. Also, the topics are
explained really well and you do not need to look up additional material.
Also, I really appreciate that he took the time to derive those equations
while others just drop the results.

~~~
kevas
I'm started the Deep Learning course last night and I too think it's really
good. After you finished the series of courses, what did you move on to?

~~~
silverdrake11
fast.ai

------
timlod
I'm currently taking the course "Audio Signal Processing for Music
Applications", a joint course from the Pompeu Fabra University in Barcelona
and Stanford, taught mainly by one of the leading figures in music technology,
Xavier Serra.

I think the pacing is great even for people who are not yet into DSP; every
lecture teaches fundamental concepts that build on top of each other, and many
insightful examples are given (listening to waveforms, looking at
spectrograms). I'm now in week 5 (I just watch the lectures at my own pace,
e.g. so far I don't need the programming part of the course), and I've already
learned a lot.

------
_jal
I personally found this to be a great one.

[https://www.coursera.org/learn/psychological-first-
aid](https://www.coursera.org/learn/psychological-first-aid)

Having even passing familiarity with a way to think about helping people in
crisis is extremely useful when you're in the moment.

~~~
derangedHorse
Now that looks like an interesting recommendation! It looks like it can offer
information I can’t find elsewhere, unlike most of Coursera’s other classes

------
xfer
I am taking the Modelling series([https://www.coursera.org/learn/basic-
modeling](https://www.coursera.org/learn/basic-modeling)) and Discrete
optimization([https://www.coursera.org/learn/discrete-
optimization](https://www.coursera.org/learn/discrete-optimization)). Great
way to get your feet wet in the world of NP-hard problems.

~~~
dowakin
Discrete optimization is the best course for me. It's really challenging one.
I spend about a month for getting A score for all tasks - but it's rewarding
experience.

I miss professor Pascal. I hope he will create a second course!

~~~
hgoury
I took watched some of the lectures and did a few exercises when I had a
similar course at University, it was great indeed.

------
carlosgg
Robert Sedgewick's courses, including Algorithms Part 1 and Part 2.

[https://www.coursera.org/instructor/~250165](https://www.coursera.org/instructor/~250165)

~~~
sidcool
Can't recommend enough. I am currently doing this and loving it.

------
WillPostForFood
Loved Model Thinking, taught by Scott Page at UM. Good for the current model
dependent times as well.

[https://www.coursera.org/learn/model-
thinking](https://www.coursera.org/learn/model-thinking)

 _We live in a complex world with diverse people, firms, and governments whose
behaviors aggregate to produce novel, unexpected phenomena. We see political
uprisings, market crashes, and a never ending array of social trends. How do
we make sense of it? Models. Evidence shows that people who think with models
consistently outperform those who don 't. And, moreover people who think with
lots of models outperform people who use only one. Why do models make us
better thinkers? Models help us to better organize information - to make sense
of that fire hose or hairball of data (choose your metaphor) available on the
Internet. Models improve our abilities to make accurate forecasts. They help
us make better decisions and adopt more effective strategies. They even can
improve our ability to design institutions and procedures. In this class, I
present a starter kit of models: I start with models of tipping points. I move
on to cover models explain the wisdom of crowds, models that show why some
countries are rich and some are poor, and models that help unpack the
strategic decisions of firm and politicians._

 _The models covered in this class provide a foundation for future social
science classes, whether they be in economics, political science, business, or
sociology. Mastering this material will give you a huge leg up in advanced
courses. They also help you in life. Here 's how the course will work. For
each model, I present a short, easily digestible overview lecture. Then, I'll
dig deeper. I'll go into the technical details of the model. Those technical
lectures won't require calculus but be prepared for some algebra. For all the
lectures, I'll offer some questions and we'll have quizzes and even a final
exam. If you decide to do the deep dive, and take all the quizzes and the
exam, you'll receive a Course Certificate. If you just decide to follow along
for the introductory lectures to gain some exposure that's fine too. It's all
free. And it's all here to help make you a better thinker!_

------
the_snooze
Securing Digital Democracy [https://www.coursera.org/learn/digital-
democracy](https://www.coursera.org/learn/digital-democracy)

I went through this not long after it was first offered following the 2012
elections, and it introduced me to the amazing world of security and human
factors. There's more to secure systems design than just smart engineering.
You have to give a lot of attention to people and priorities, and elections
are a great place to see that in action.

~~~
notechback
Seconded I've taken a number of courses and this is by far the best mooc I've
taken.

------
mmm_grayons
Cryptography I by Dan Boneh:
[https://www.coursera.org/learn/crypto](https://www.coursera.org/learn/crypto)

It's a great introduction to fundamental concepts. After you finish, I'd
recommend reading this book he co-authored, which goes into more detail and
covers more advanced concepts:
[https://toc.cryptobook.us/book.pdf](https://toc.cryptobook.us/book.pdf)

------
mkolodny
Design: Creation of Artifacts in Society is my favorite course I've ever
taken:

[https://www.coursera.org/learn/design](https://www.coursera.org/learn/design)

It's taught by Karl Ulrich, a UPenn/Wharton professor/Vice Dean who helped
design the Xootr scooter, Gushers, and many other awesome products. He teaches
most of the course in his garage. Taking the course feels like you're his
apprentice.

------
Dowwie
Coursera is great but you're going to miss a lot of opportunities by limiting
yourself to just that platform.

For instance, it hasn't been widely advertised, but you can essentially take
Steven Pinker's 2020 course at Harvard on Rationale:
[https://stevenpinker.com/classes/rationality-
gened-1066](https://stevenpinker.com/classes/rationality-gened-1066)

There's upwards of 20 hours of video on this course alone. You don't get that
kind of depth from most Coursera MOOCs. Further, the syllabus helps narrow
down a vast subject to a few months of effort and there is no better design
for learning it.

Critical reasoning skills are essential! Why not learn from one of the great
thinkers on the subject?

This course has the potential of ascending to the upper echelon of MOOCs. I
really hope that the content doesn't get taken down. It doesn't seem
downloadable..

~~~
Eugeleo
Looks great! Is this the rationality often mentioned (and propagated) on
LessWrong, Slate Star Codex and similar?

~~~
Dowwie
Yes it is

------
int32767
I really enjoyed the course on the Science of Exercise -
[https://www.coursera.org/learn/science-
exercise](https://www.coursera.org/learn/science-exercise).

I always wondered if there was a comprehensive way to understand how different
fitness regimes and diets actually help or don't help. This course was amazing
and helped my understand the fundamentals. A bit technical - goes into the
basics of biology, but even without that information, this was a great course.
The instructor is Dr. Robert S. Mazzeo, who has been studying, researching and
teaching in the field of exercise science for over 40 years.

I have actually applied several of the principles in my workout regime and
started to see the effects over the last few months. I highly recommend this
one.

~~~
hnrodey
Not sure if I'll follow through on this but this was a great recommendation as
I had no clue of its existence. Thank you very much for taking the time to
recommend this and exercise science is a budding interest for me.

------
seankross
I wrote this course, an introduction to using the command line:
[https://www.coursera.org/learn/unix](https://www.coursera.org/learn/unix)

~~~
int32767
Oh! Speaking of command line and the basics, this one from MIT is amazing.
Covers all the basics.

The Missing Semester of Your CS Education -
[https://missing.csail.mit.edu/](https://missing.csail.mit.edu/)

Contents: Course overview + the shell, Shell Tools and Scripting Editors
(Vim), Data Wrangling, Command-line Environment, Version Control (Git),
Debugging and Profiling, Metaprogramming, Security and Cryptography

------
smabie
Let me recommend you an udacity course instead. This is hands down the best
course I've ever taken in my life:

AI for Trading [https://www.udacity.com/course/ai-for-trading--
nd880](https://www.udacity.com/course/ai-for-trading--nd880)

Includes an introduction to finance/markets, and goes into strategies, multi-
factor models, and deep learning. Great projects too!

~~~
chrisatumd
It looked interesting - is it really $400 a month for access to the course, or
is there some other way to just take the course without some kind of
certificate?

~~~
smabie
I'm not sure, but I took really good notes (along with good pictures from the
videos). I have them in org and html: [https://github.com/smabie/udacity-AI-
trading-notes](https://github.com/smabie/udacity-AI-trading-notes)

------
goose847
University of Pennsylvania has an amazing course on single variable calculus.

Don't let the idea of doing 'basic' calculus turn you away as it is an
incredibly tough course. The reason it can be so challenging and the reason I
find it so incredible is that it teaches Calculus through the lenses of Taylor
Series. Very different to other Calculus courses and as someone who hated my
first year university maths course it's helped me really come to appreciate
the beauty of it!

Here's the link to the first course of 5:

[https://www.coursera.org/learn/single-variable-
calculus](https://www.coursera.org/learn/single-variable-calculus)

~~~
polomi
I strongly recommend Robert Ghrist's other courses as well, they're fantastic.

* Multivariable calculus (a linear algebra based approach, and a very nice intro to differential forms)

* Applied dynamical systems (ongoing, started recently)

[https://www.youtube.com/channel/UC5N5pRddyicAX1QJyJjIIdg](https://www.youtube.com/channel/UC5N5pRddyicAX1QJyJjIIdg)

~~~
goose847
That’s fantastic! Thanks for sharing!

------
BakaKuna
I loved 'Classical Sociological Theory'. It introduces the ideas of 8
'sociological' thinkers from Bernard Mandeville to Norbert Elias. The course
uses the medium of a MOOC by providing insightful pictures and the course
references interesting source material.

The course that brings me the most in terms of concepts I keep coming back to
in everyday live is 'Introduction to Psychology':
[https://www.coursera.org/learn/introduction-
psychology](https://www.coursera.org/learn/introduction-psychology)

I must confess I always find it quite hard to take psychology very serious,
but this course does a good job at cutting to the bone of what psychology is
about and refrains from making unfalsifiable statements.

EDIT: Almost forgot Astronomy: Exploring time and space:
[https://www.coursera.org/learn/astro](https://www.coursera.org/learn/astro).
It comes with a very awesome free online book/website.

------
bcrosby95
I took it a while ago, and it was a ton of work, but I really liked
[https://www.coursera.org/specializations/probabilistic-
graph...](https://www.coursera.org/specializations/probabilistic-graphical-
models)

~~~
tasubotadas
I took it relatively recently but I have mixed feelings about it. While the
topic itself is very interesting and they have some interesting exercises, the
explanations in the videos are seriously lacking.

There are big jumps in reasoning and explanations so you'll need to rely on
external material quite a bit (I've used Bayesian Reasoning by Barber) Also,
exercises are presented in Matlab/Octave which makes them a pain to work with.

After completing the specialization, I've almost felt that you could just do a
course that explains this course.

------
noobrunner
[https://www.coursera.org/learn/genetics-
evolution](https://www.coursera.org/learn/genetics-evolution) Beginners
level.Dr. Noor is an excellent instructor.

~~~
Eugeleo
Thanks! The teacher makes or breaks the course, and that is exactly why I
asked for personal recommendations.

As an aside, the world of genetics (and molecular biology in general) is
beyond fascinating. I remember coming home after one the 5th or 6th lecture on
Cell biology and thinking "wow, take your worst spaghetti code and imagine the
pasta becomes sentient --- that is us".

~~~
noobrunner
very well said ! I am wondering if anyone here has recommendations on where to
go next after I finish this course ?

------
ForHackernews
It's not on Coursera, but Caltech's Yaser Abu-Mostafa offers "Learning from
Data" on his own website
[https://work.caltech.edu/telecourse.html](https://work.caltech.edu/telecourse.html)
and it's intermittently on EdX [https://www.edx.org/course/learning-from-data-
introductory-m...](https://www.edx.org/course/learning-from-data-introductory-
machine-learning)

This is far and away the best MOOC I've ever taken. The class is genuinely
challenging. It's a real Caltech undergraduate course, and you can't get away
with copy-pasting code or just keep resubmitting until you pass the grader.
The course is focused on real understanding of what's going on mathematically,
not just learning to use some library API.

------
edem
I know that you didn't ask for this but I think this is the best course on
Coursera hands down:

[https://www.coursera.org/learn/model-
thinking](https://www.coursera.org/learn/model-thinking)

I've larned much more from this than from anything else on this site.

~~~
techsin101
Any examples of what makes it good

------
hagope
Coursera has great content from Industry partners (Google Cloud, Amazon AWS,
IBM etc) that teach everything you need to know for hacking in cloud. These
skills are not widely taught in University, but skills are highly valued in
the Tech industry. Three specializations (a collection of courses) that are
hands-on and I would highly recommend 1.)
[https://www.coursera.org/specializations/aws-
fundamentals](https://www.coursera.org/specializations/aws-fundamentals) 2.)
[https://www.coursera.org/specializations/gcp-data-machine-
le...](https://www.coursera.org/specializations/gcp-data-machine-learning) 3.)
Anything from deeplearning.ai [disclosure: I work at Coursera]

------
sonabinu
I would start with 'Learning how to Learn' \-
[https://www.coursera.org/learn/learning-how-to-
learn](https://www.coursera.org/learn/learning-how-to-learn)

~~~
leandron
I took it a few years back. Highly recommended.

------
mekane8
I would absolutely love to hear someone's experience taking this course:
[https://www.coursera.org/specializations/coding-for-
managers...](https://www.coursera.org/specializations/coding-for-managers/)

I probably won't have time to sit through it, but I've taken a course from
this instructor in the past and he is pretty good. I'm really curious to know
how he explains coding and engineering principles to "managers, designers and
entrepreneurs".

------
huntermeyer
Introduction to TensorFlow:

[https://www.coursera.org/learn/introduction-
tensorflow](https://www.coursera.org/learn/introduction-tensorflow)

Data Scientist's Toolbox:

[https://www.coursera.org/learn/data-scientists-
tools](https://www.coursera.org/learn/data-scientists-tools)

------
nikofeyn
programming languages (parts a, b, and c) by dan grossman

[https://www.coursera.org/learn/programming-
languages](https://www.coursera.org/learn/programming-languages)

introduces the underpinnings of programming languages via standard ml, racket,
and ruby.

~~~
jbotz
I second this recommendation. A really good course, and if you do all 3 parts
it's really the equivalent of a full university course. Covers the main
concepts in modern programming languages, such static vs. dynamic typing, OO
vs functional, and does so I consdierable depth, with reasonably challenging
programming projects. Even if you think you already know this stuff, it's a
good review and I guarantee you'll learn a few new things.

Also, Dan is a good professor and is really enthusiastic about the subject.

~~~
nikofeyn
yep, it's a very fun course and very well organized, including code reviews
for homework. i fixed some issues found in mine and enjoyed reviewing others'
work. i do wish there were programming assignments for sml's module system
though. that part felt a bit tacked on.

i still need to go back and finish the ruby section. at that point in the
course, i got distracted with other things.

------
matt_morgan
Unstuck to your categories, Jonathan Biss's course on Beethoven's sonatas is
fantastic.

[https://www.coursera.org/instructor/jonathanbiss](https://www.coursera.org/instructor/jonathanbiss)

------
digiaditya
Edx is also not bad: [https://www.edx.org/course/subject/computer-
science](https://www.edx.org/course/subject/computer-science)

------
credit_guy
Two courses taught by faculty at the Russian institute HSE (Higher School of
Economics).

1\. How to Win a Data Science Competition
[https://www.coursera.org/learn/competitive-data-
science](https://www.coursera.org/learn/competitive-data-science)

2\. Bayesian Methods for Machine Learning
[https://www.coursera.org/learn/bayesian-methods-in-
machine-l...](https://www.coursera.org/learn/bayesian-methods-in-machine-
learning)

------
udayj
Had been working on [https://www.tutorack.com/](https://www.tutorack.com/) for
a while - aggregates online resources (not just MOOCs). Haven't updated it in
sometime but you should find something useful

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jhymn
I recently took a Coursera course on Schizophrenia and found it fascinating.
YMMV of course.

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carlosgg
The first 3 courses of the Statistics with R specialization, taught by Dr.
Mine.

[https://www.coursera.org/specializations/statistics](https://www.coursera.org/specializations/statistics)

------
wheeliegeek
Learning how to learn

[https://www.coursera.org/learn/learning-how-to-
learn/](https://www.coursera.org/learn/learning-how-to-learn/)

------
fbru02
I really liked the approximation algorithms from a french university

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DrNuke
Ok but do you need a course meant as a vocational, subject-specific training
or something more liberal that helps you think better for the long run? I
would go for the latter.

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master_yoda_1
most of the courses on coursera are for uninitiated and have very shallow
content (there are some rare exception). So if you like you can search for a
good book or some video lecture from good university. like this is for
statistical learning "[https://online.stanford.edu/courses/sohs-
ystatslearning-stat...](https://online.stanford.edu/courses/sohs-
ystatslearning-statistical-learning")

~~~
randcraw
Broken link due to quote marks. Great suggestion otherwise.

[https://online.stanford.edu/courses/sohs-ystatslearning-
stat...](https://online.stanford.edu/courses/sohs-ystatslearning-statistical-
learning)

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exdsq
I’ve started working through the Verification series by EIT which have been
challenging and interesting. If you’re interested in formal verification,
check them out.

~~~
manu3000
Can you please post a link to this?

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evancox100
Princeton’s Computer Architecture course is great.

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Tomte
Dan Boneh's Crypto II. ;-)

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edimaudo
epidemics, learning how to learn, algorithms 1 & 2

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droithomme
> bioinformatics

The Honors Track of the UCSD series is really great.

[https://www.coursera.org/specializations/bioinformatics](https://www.coursera.org/specializations/bioinformatics)

It's super hard and as a side effect you learn a ton about very interesting,
amazing, and useful algorithms that you'd never even hear about in a top notch
CS program.

~~~
Eugeleo
That sounds great! I'll check it out tomorrow.

Some people here in Europe take bioinformatics as a shorthand of "database
management, pipeline construction, and scaffold building" \--- I'm glad to see
the course is more algorithm oriented (maybe with a bit of DS thrown in as
well).

