15 ms·

Ask HN: Top Coursera Courses?

486 points by joshlk 6y ago

In any field that “interesting” to HN

tdsamardzhiev 6y ago
I think Dan Grossman's Programming Languages courses are amazing if you have slept through the subject in university: https://www.coursera.org/learn/programming-languages https://www.coursera.org/learn/programming-languages
- prezjordan 6y ago
  +1! This is a three-parter and it was such a fun hobby for a few weeks when quarantine was kicking up. I had played with plenty of languages before but didn't realize the gaps in my knowledge. Would recommend.
- Lewton 6y ago
  I did this course 5+ years ago and I still remember it fondly! I can pretty confidently say that it made me a better developer
- agumonkey 6y ago
  I wish there was a follow up. Brown published their book online, but it's not as fun without a structure.
- MattyMc 6y ago
  As someone who learned to program outside of college, this course was one of my favorites.
- brudgers 6y ago
  I took it the second time it was offered. One of the main reasons was it was as an excuse to learn Emacs. Does anyone know if the course still encourages using Emacs?
  - bagelman 6y ago
    it does!
- bagelman 6y ago
  Great class that really challenged me as a self-taught programmer. Rewarding assignments that pushed back the basics you often find in MOOCs
- namborita 6y ago
  These are absolute gems! I remember how bummed I felt watching the last video of the last course because it was ending.
joshlk 6y ago
Nand to Tetris: how a computer is built from the ground up. Starting from nand logic gates all the way to OO programming https://www.coursera.org/learn/build-a-computer https://www.coursera.org/learn/build-a-computer
- Tomte 6y ago
  The course is good, the book is better, in my opinion. Although it covers the same, but I like its presentation much better than the video course. Nisam/Schocken: "The Elements of Computing Systems" I have only finished the hardware part, so far, but skimming the rest I can't find Tetris anywhere. Is that really missing, although it's in the title? (I know that you can program Tetris on the machine you build in the course, but is it an exercise somewhere?
  - captn3m0 6y ago
    One section asks you to learn Jack (The high-level programming language) by writing a medium-complexity program. The goal of the exercise is not to get proficient in Jack (which is a Java-like-language), but to just learn it well enough to implement the compiler. I wrote a Tic-Tac-Toe variant - but you could write anything, including Tetris.
  - troupe 6y ago
    On Coursera, if I remember right, the first course gets you to the point where you have a CPU that can run machine language and an assembler. They give you an assembly version of Tetris that will run on what you built. In the second course you build the programming language that could be used to write Tetris, though I don't think you actually go through it as an exercise.
  - sn9 6y ago
    The second edition of the book is actually slated for release in July. You can preorder it on Amazon.
- SilasX 6y ago
  Seconding this. It's the most fun I've ever had on a technical project (with the possible exception of tptacek's microcorruption.com), and really opened my eyes to all the problems you have to solve to get a working computer. Note: you can also complete all the course materials just by going to nand2tetris.org. My presentation slides promoting nand2tetris to the Austin python group: https://docs.google.com/presentation/d/1fGf2eZVOM2lHL8hFVyd2QOH-7wf0QpvVJy79gGwCScc/edit https://docs.google.com/presentation/d/1fGf2eZVOM2lHL8hFVyd2...
commonturtle 6y ago
Scott Page's Model Thinking course: https://www.coursera.org/learn/model-thinking https://www.coursera.org/learn/model-thinking. Broad overview of how to think in models to understand the world around you.
- joshlk 6y ago
  What does that mean to think in models?
  - ayewo 6y ago
    Models are tools to help us reason clearly about the world. They help us deal with complexity in manageable chunks by focusing on salient parts of a problem, rather than the whole. From my course notes, a nearly comprehensive summary of how the social sciences use models was presented: 16 uses of modeling outside prediction include from Epstein, Joshua M. (2008). Why Model?. Journal of Artificial Societies and Social Simulation: 1. Explain (very distinct from predict) 2. Guide data collection 3. Illuminate core dynamics 4. Suggest dynamical analogies 5. Discover new questions 6. Promote a scientific habit of mind 7. Bound (bracket) outcomes to plausible ranges 8. Illuminate core uncertainties 9. Offer crisis options in near-real time 10. Demonstrate tradeoffs / suggest efficiencies 11. Challenge the robustness of prevailing theory through perturbations 12. Expose prevailing wisdom as incompatible with available data 13. Train practitioners 14. Discipline the policy dialogue 15. Educate the general public 16. Reveal the apparently simple (complex) to be complex (simple)
  - alisonkisk 6y ago
    Think scientifically/mathematically. It what most people who hang out HN do intuitively, but most of the general public does not. (Like how Dr Fauci talks about COVID-19 vs how Donald Trump does).
- aoshifo 6y ago
  For me, this was also the most interesting course. But I don't think you can still access it (I tried a couple of months ago to revisit it). But Scott Page also has a book out on the topic "The Model Thinker", which covers most of the course.
mbaytas 6y ago
Scott Klemmer’s HCI- and design-related courses: https://www.coursera.org/instructor/~1250 https://www.coursera.org/instructor/~1250
Mimmy 6y ago
Interesting prior discussion from 2018 https://news.ycombinator.com/item?id=16745042 https://news.ycombinator.com/item?id=16745042
- tsjq 6y ago
  Thanks
samvher 6y ago
I quite liked "How to win a data science competition" (https://www.coursera.org/learn/competitive-data-science https://www.coursera.org/learn/competitive-data-science) where I learned a lot about validation strategies and machine learning on tabular data. The course has its own Kaggle competition. I also really liked "Discrete optimization" (https://www.coursera.org/learn/discrete-optimization https://www.coursera.org/learn/discrete-optimization). At the time that I took it it also had a competitive element where you would solve optimization problems and there was a leader board comparing all the students in the current batch. That was when courses still started in batches and were free so the experience would probably no longer be the same, unfortunately.
- light_hue_1 6y ago
  > I quite liked "How to win a data science competition As a machine learning researcher I am on the one hand glad that folks are learning more about the topic. On the other hand, this is totally the wrong approach and it will teach you the wrong lessons. The idea that you can just treat data as a uniform dump of tables and that grinding your way to high numbers is somehow worthwhile is simply terrible. The resulting systems won't work well in the real world and they produce horrific explanations of what is going on. This class teaches you not just the wrong tools, like boosting, it teaches you the wrong mental model. I really can't think of a worse introduction to ML than this class. Even not knowing anything would actually be better.
  - samvher 6y ago
    Interesting. I definitely would not recommend this course as an only course in machine learning or indeed as an introduction, and I see where you’re coming from with the wrong mental models. I can’t be sure that I do have the right ones but I have taken a number of other courses as well and my sense is they’re ok. My main takeaway from the course was definitely not that just grinding away for higher numbers is the right thing to do (but it might be a necessary evil in a competition context). The key thing I learned here was much more about paying very close attention that your validation strategy and your testing strategy are compatible because there are many ways you can mess it up, making your models valid in-sample only. Most of the other things I had done before were also more around SVMs and neural networks and getting some experience with decision tree based algorithms was interesting.
oli5679 6y ago
I really enjoyed Tim Roughgarden's 'Algorithms' specialisation. The first half are actually on Stanford's online learning platform for free. https://www.coursera.org/specializations/algorithms https://www.coursera.org/specializations/algorithms
- thecleaner 6y ago
  Highly recommend this course. Good coverage of topics and the explanations help build intuition.
- bhrgunatha 6y ago
  I took his 2 algorithm courses on Coursera's original platform. They were stellar. In particular making practical problems that have a calculable answer that you implement yourself in whatever language you choose and check as part of the course. As opposed to having some online interpreter for some specific language. That was then hosted on Stanford's own Lagunita platform (based on the edX platform I think.) Stanford then split those 2 courses into 4 on Coursera's new platform - the same material I believe but packaged differently. Stanford then closed its Lagunita platform and those original 2 courses are now offered on edX. A similar story with Alex Aiken's excellent Compiler course and Jeffrey Ullman's Automata course too. I'm not even sure if they are still available on Coursera or not. [1] https://www.edx.org/course/algorithms-design-and-analysis https://www.edx.org/course/algorithms-design-and-analysis [2] https://www.edx.org/course/algorithms-design-and-analysis-part-2-2 https://www.edx.org/course/algorithms-design-and-analysis-pa... [3] https://www.edx.org/course/compilers https://www.edx.org/course/compilers [4] https://www.edx.org/course/automata-theory https://www.edx.org/course/automata-theory
- BossingAround 6y ago
  What level of math would you recommend for the courses? This is always a difficult question, because it's always "high school level math" which is rarely true. Then again, some algo courses focus highly on math and proofs while others focus more on implementation.
- rskirkpatrick 6y ago
  I prefer the Algorithms course by Princeton but I still really like this course. The deep dive into the mathematical proofs and timing of these algorithms is what gives this course an advantage over Princeton’s course.
etherio 6y ago
Not coursera but I'd definitely recommend Helsinki university's Elements of AI course [0]. It's quite accessible and a good introduction to artifical intelligence. [0]: https://www.elementsofai.com/ https://www.elementsofai.com/
adeel_siddiqui 6y ago
Programming Languages, Dan Grossman, UW. https://www.coursera.org/learn/programming-languages https://www.coursera.org/learn/programming-languages It is a 3 part course and a bit more intensive than other courses on Coursera with challenging assignments. It helped me gain a deeper understanding of statically vs dynamically typed languages. Designing a tiny language in Part B is the best part of the course. Concludes with a nice comparison between OOP and functional languages.
- vvillena 6y ago
  Did this one when it was just one single course. The content is great, but the best thing by fat is the teacher. Dan Grossman is a natural teaching talent, and this course shows how one single teacher can make a difference.
  - utxaa 6y ago
    dan is awesome. nice guy too.
- dzhiurgis 6y ago
  Did that too and it totally changed how understand programming (was a newbie back then).
- rskirkpatrick 6y ago
  Thanks for the suggestion. I will check it out.
yawz 6y ago
Dr Barbara Oakley’s “Learning How to Learn” [0] is great. Edit: It gives an important understanding on how our minds function and how we learn, which, I think, forms the basis of effective work. Knowing how to work, and being an effective learner are incredibly important qualities in life. [0] https://www.coursera.org/learn/learning-how-to-learn https://www.coursera.org/learn/learning-how-to-learn
- joshlk 6y ago
  What’s good about it?
  - thecleaner 6y ago
    You can get a sample out of her Google talk on YouTube. Basically the course tells you ideas about how to read/manage time to learn things more efficiently.
    - Ma8ee 6y ago
      And most importantly, why you should study and manage your time in certain ways. A lot of things in that course feels like it fairly obvious when you hear it, but often you might not have thought in those directions, and often it helps to get those things spelled out. If I had had that course in my early teens that would have helped me a lot.
      - thecleaner 6y ago
        I really enjoyed the part about recollecting vs rereading. This changed my perspective on how to read things. I have noticed I read less nonsense and retain more of the important topics. Also tried it with software docs. Although recollecting API names didnt help me make better software decisions but it came in handy while writing code. A bit of fluency helped reduce friction since I could code with less context switches.
        Ma8ee 6y ago
everythingswan 6y ago
The Python for Everybody course was great. I was excited to complete it (well, the first 3 courses in the roadmap): https://www.coursera.org/specializations/python https://www.coursera.org/specializations/python As a non-programmer but a decent mather, I thought it presented the materials in a way that was easy to understand. In my mid-thirties now, I feel like I could have handled this at 18 just fine--but not in a patronizing way. It was just very clear and the professor had a good sense of humor. I just built my first time-saving Python program and it felt really satisfying. I built a few others that were cool but none actually saved me time. Very satisfying! At the end of the 3 courses (~60 hours) and some additional tinkering (~40 hours), I had the skills and that's pretty cool.
- cdkee 6y ago
  +1 for Dr Chuck! Echo your sentiments exactly. Had I taken this course when I was 18, I surely would have gone for a CS degree.
- alisonkisk 6y ago
  As someone who has been both 18 and 30, 18 is a much easier time to learn a programming language.
arcturus17 6y ago
Princeton's and Stanford's Algorithms are fantastic.
- passwordreset 6y ago
  I was disillusioned by Princeton's Algorithms course when I took it. I felt like I was fighting too hard with eccentricities of Java than actually learning about algorithms. In retrospect, I was wrong, because one of the things I realized that it taught me was that implementation details of algorithms are _hugely_ important, and can cause drastic differences in time and memory utilization. I can easily forget the details, but I haven't forgotten the experience of hacking out my stupid mistakes until the implementations fit the requirements.
  - arcturus17 6y ago
    That was a learning for me too, but I thoroughly enjoyed the psets. I don't mind Java - setting everything up can be annoying but I find it fairly straightforward and its massive standard library comes in handy for a class like this.
kassas 6y ago
"Modern Big Data Analysis with SQL Specialization" by Cloudera is awesome. It discusses Hadoop, Hive, Impala and Big Data and the instructors are great. It is rated 4.8/5.0 https://www.coursera.org/specializations/cloudera-big-data-analysis-sql https://www.coursera.org/specializations/cloudera-big-data-a...
jschulenklopper 6y ago
https://www.classcentral.com/collection/top-free-online-courses https://www.classcentral.com/collection/top-free-online-cour... (Not just on Coursera, but also others. You can filter for the Coursera ones.)
- afarzad 6y ago
  Not Coursera but I really enjoyed the "Intro to Complexity" course from the Sante Fe Institute; it's highly recommended on classcentral. It gives a broad overview of how complex systems emerge from simple phenomenon and shows how cross-disciplinary some of these insights are. https://www.complexityexplorer.org/courses/104-introduction-to-complexity https://www.complexityexplorer.org/courses/104-introduction-...
- 9test123456789 6y ago
  nb
atrisx 6y ago
Intro to Psychology: https://www.coursera.org/learn/introduction-psychology https://www.coursera.org/learn/introduction-psychology The Modern World, Part One: Global History from 1760 to 1910: https://www.coursera.org/learn/modern-world https://www.coursera.org/learn/modern-world (2nd part is as great as the first one)
maurits 6y ago
My personal favorite, Statistical Mechanics and Computations.[1]. Excelled introduction to MCMC methods, lots and lots of python programs and filmed against a green screen. Obligatory, Stanford CS231n: Convolutional Neural Networks for Visual Recognition [2] The assignments are excellent and will let you implement a deephish network from practically scratch, before diving into modern frameworks and applications. [1]: https://www.coursera.org/learn/statistical-mechanics https://www.coursera.org/learn/statistical-mechanics [2]: http://cs231n.stanford.edu/index.html http://cs231n.stanford.edu/index.html
Tepix 6y ago
I thought "The science of the solar system" by Mike Brown was an excellent introduction. https://www.coursera.org/learn/solar-system https://www.coursera.org/learn/solar-system
- vvm 6y ago
  I second this, one of the best courses I attended on coursera.
krtkush 6y ago
Model Thinking by Scott E. Page - https://www.coursera.org/learn/model-thinking/home/welcome https://www.coursera.org/learn/model-thinking/home/welcome
joshlk 6y ago
Has anyone tried either?: - "Fundamentals of Parallelism on Intel Architecture" https://www.coursera.org/learn/parallelism-ia https://www.coursera.org/learn/parallelism-ia - "Introduction to High-Performance and Parallel Computing" https://www.coursera.org/learn/introduction-high-performance-computing https://www.coursera.org/learn/introduction-high-performance...
dimmuborgir 6y ago
Audio Signal Processing for Music Applications Professor Xavier Serra[1] is a highly respected veteran in the field. [1] https://en.m.wikipedia.org/wiki/Xavier_Serra https://en.m.wikipedia.org/wiki/Xavier_Serra
mportela 6y ago
Another thread from earlier this year with pretty good recommendations: https://news.ycombinator.com/item?id=22826722 https://news.ycombinator.com/item?id=22826722
rajbiswas125 6y ago
Andrew NG Deep Learning courses were nice, especially for an absolute beginner.
iou 6y ago
Cryptography 1, time well spent. ~3000 reviews at 4.8 stars https://www.coursera.org/learn/crypto https://www.coursera.org/learn/crypto
- GekkePrutser 6y ago
  +1 for this... Really good. Did it years ago and it was all very clear to me. However as I don't use this in daily life I pretty much lost all the knowledge again :)
  - stockkid 6y ago
    Same. Having finished the course years ago, I remember most vividly the following: never implement your own crypto. Not many details survived the time but it was intellectually rewarding.
- verroq 6y ago
  Just don’t hold your breath for Cryptography 2
  - latenightcoding 6y ago
    I was hoping it would finally be available this year. Now I think it's never going to happen.
    - Thorentis 6y ago
      The course is apparently being released when the accompanying book is complete. The book is free, and you can see the current version here: https://cryptobook.us/ https://cryptobook.us/
      - iou 6y ago
        It's super dense though, even with a math background I struggled to make headway.
  - 6y ago
Nowado 6y ago
I have no idea how 'Machine Learning' from Ng is not mentioned. It's fine in teaching you introductory (although it seems to cover more basics than a lot of other courses do, somehow) ML. But more importantly, it's a well designed course. You can see how each piece uses previous pieces and how it solves problems and edge cases not covered earlier.
- iou 6y ago
  Yes!! Though I did it a long time ago and I'm not sure if it's been modernised for current ML norms?
  - Nowado 6y ago
    AFAIK it wasn't. Ng just makes new courses for new methods. That said, I'm yet to see better coverage of that topics (If someone knows, I'd really like to get them. I forget pieces every now and then, and having more efficient refresh method is always welcome).
    - visarga 6y ago
      I hope everyone was referring to Andrew's blackboard course: https://www.youtube.com/watch?v=UzxYlbK2c7E&list=PLA89DCFA6ADACE599 https://www.youtube.com/watch?v=UzxYlbK2c7E&list=PLA89DCFA6A... instead of the one that started Coursera: https://www.youtube.com/watch?v=PPLop4L2eGk&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN https://www.youtube.com/watch?v=PPLop4L2eGk&list=PLLssT5z_Ds...
- omarhaneef 6y ago
  I appreciate his attention to pedagogy. Even small things like noticing that students learn better with Matlab/Octave than with R or Python is the kind of observation that takes a combination of knowledge, effort and caring about teaching.
  - BoiledCabbage 6y ago
    I could be wrong, but I think it has nothing to do with that, and now to do with the course being so old that R and Python weren't the standard ML languages yet.
veganjay 6y ago
I can think of many - I have taken several starting since 2013. The tricky thing is that Coursera classes seem to get merged, re-mashed or otherwise re-branded. And as such only one currently is listed in my "Completed" courses section of my profile. Having said that and with the caveat that these probably changed since I taken them, I recommend the following: - Cryptography - https://www.coursera.org/learn/crypto https://www.coursera.org/learn/crypto - great introduction to the fundamentals and math behind cryptography. A lot of theory but also some practical exercises. This is my top recommended. - Machine Learning - https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning - a good introduction to the basic of machine learning; focuses on octave/matlab and does not dive into frameworks like scikitlearn or tensorflow - Introduction to Interactive Programming with Python - https://www.coursera.org/learn/interactive-python-1 https://www.coursera.org/learn/interactive-python-1 - I took a course from Rice University on Python programming through making games that was fun. As far as I can tell, this is the modern incarnation in two parts. - Software Security - https://www.coursera.org/learn/software-security https://www.coursera.org/learn/software-security - goes into stack / overflow exploits, tools for testing, and web-based attacks - Functional Programming Principles in Scala - https://www.coursera.org/specializations/scala https://www.coursera.org/specializations/scala - this was a good introduction to scala and functional programming - it got me thinking in a different way - C++ for C Programmers - https://www.coursera.org/learn/c-plus-plus-a https://www.coursera.org/learn/c-plus-plus-a - I think this was the first coursera class I took. This course dove into the C++ STL and a lot of modern features introduced in C++11.
- mlinksva 6y ago
  > as such only one currently is listed in my "Completed" courses section of my profile. That's surprising to me: wouldn't Coursera want learners to be reassured that whatever signalling benefit there is to completing a course will remain forever? I took a few courses in 2013 just to see what MOOCs are really like and completed two (Programming Languages, as taken by many here, and Introduction to Mathematical Thinking, which IIRC was mostly about logic) which indeed are not listed under "completed" in my profile. I found them at https://www.coursera.org/accomplishments https://www.coursera.org/accomplishments though.
ra7 6y ago
Economics of Money and Banking by Perry Mehrling - https://www.coursera.org/learn/money-banking https://www.coursera.org/learn/money-banking Great course to learn about monetary systems, central banks and its effects on financial markets.
repsilat 6y ago
I took a bunch back in the day, and I liked Economics of Money and Banking[1] (by Perry Mehrling) more than most other courses. It's partly a history of the American financial system, and partly a tour of some modern financial instruments and institutions. The focus is on how things work and why they're designed as they are, and not so much on how things are priced. Deposits, bonds, commodity futures, central banks, how it all fits together, what purpose it all serves -- how it's not just gambling or an abstract game used to extract money from the productive economy. One of the stated aims of the course is to get you in a position where you can read the Financial Times without going cross-eyed, and it works really well to give a clarifying framework for understanding market concepts outside the course's scope. Another I really liked was "The Modern and the Postmodern" by Michael Roth. I don't know if that course would work well "at your own pace" though, the reading and peer essay feedback was a big part of it. 1: https://www.coursera.org/learn/money-banking https://www.coursera.org/learn/money-banking
- littlestymaar 6y ago
  I came here to recommend the same course. It's really well done and covers not only conventional banking but also covers quantitative easing post financial crisis. And the guy is also pretty funny.
- avyfain 6y ago
  I did "The Modern and the Postmodern" last year, and really enjoyed it without doing the essays/peer review. Curiously I'm now working through Mehrling's course, too. Another one I'd recommend if you enjoyed those two, although in a very different vein is Bloom's Moralities of Everyday Life, which is supposedly a psychology course, but really goes into comparative culture questions that IMO make it closer to an anthropology course. https://www.coursera.org/learn/moralities https://www.coursera.org/learn/moralities
davuinci 6y ago
Financial Markets course [0] taught by Robert Shiller (Nobel laureate) is a phenomenal course to understand the basics of financial markets. He explains how financial markets work from an engineering perspective which is an interesting approach in contrast to other similar courses. [0] https://www.coursera.org/learn/financial-markets-global https://www.coursera.org/learn/financial-markets-global
- closeparen 6y ago
  I tried this course and found it nearly unwatchable due to the editing. Rapid cuts jump around topics and rooms and days without any transitions and without any logical continuity either. Shiller frequently references things he probably said 5 minutes ago in the actual lecture, but won’t say for 10 more videos in the Coursera edit. I cannot find anyone else talking about this in the reviews; they are all glowing. Wondering if I’m crazy, if Coursera is glitching just for me, or if no one actually watched the videos.
  - soramimo 6y ago
    Here's the 2011 version of Shiller's lecture on Financial Markets on YouTube, which doesn't have this problem: https://www.youtube.com/playlist?list=PL8FB14A2200B87185 https://www.youtube.com/playlist?list=PL8FB14A2200B87185
    - closeparen 6y ago
      Thank you!
abecedarius 6y ago
I quite enjoyed https://www.udacity.com/course/design-of-computer-programs--cs212 https://www.udacity.com/course/design-of-computer-programs--... -- program design by Peter Norvig. (Disclaimer: I had a very small part in preparing it.)
- hiyer 6y ago
  +1 for this. It's quite python-specific, but I found it amazingly insightful.
elil17 6y ago
The Science of Well Being. A great course about how psychologists research human happiness and what the current state of the art suggests are the best strategies for leading a fulfilling life. https://www.coursera.org/learn/the-science-of-well-being https://www.coursera.org/learn/the-science-of-well-being
omarhaneef 6y ago
I should mention that they have a Black Friday or cyber Monday type special right now where you take a course or a month for free.
moxylush 6y ago
Thanks for the info about Machine Learning from Ng. I've been trying to find that course.
danr4 6y ago
"Introduction to Public Speaking" - Dr. Matt McGarrity I think public speaking is a very important skill that not enough people take the time to learn.
gmiller123456 6y ago
Differential Equations in Action https://www.udacity.com/course/differential-equations-in-action--cs222 https://www.udacity.com/course/differential-equations-in-act... It's not an intense differential equations course, and I don't think you even need calculus to understand or complete the exercises. It has a lot of really great, well, explained, fun exercises like computing a gravitational slingshot, computing the spread of an epidemic, then N-body problem, and others. The exercises are solved programmatically, not with math equations. America's Unwritten Constitution https://www.coursera.org/learn/unwritten-constitution https://www.coursera.org/learn/unwritten-constitution America's Written Constitution https://www.coursera.org/learn/written-constitution https://www.coursera.org/learn/written-constitution If you're American, you'll likely find both of these courses extremely interesting. What they (probably) taught you in grade/high school was very overly simplified, or just wrong. This is geared toward people who have no background in law. I don't remember there being amazing exercises to do, but there were a lot of mind blowing facts I learned about things the constitution does and doesn't cover.
x87678r 6y ago
This thread is great. I've already enrolled and given up on 20ish courses, now I have another 4 enrolled. :)
albertzeyer 6y ago
I very much enjoyed Geoffrey Hinton's course about Neural Networks. But I cannot find it anymore on Coursera? Anyway, I found it here: https://www.youtube.com/playlist?list=PLoRl3Ht4JOcdU872GhiYWf6jwrk_SNhz9 https://www.youtube.com/playlist?list=PLoRl3Ht4JOcdU872GhiYW...
- modeless 6y ago
  Surprised this isn't higher. It was absolutely incredible at the time. It was cutting edge: the now well known optimizer RMSProp was presented by Hinton in this course and not even published anywhere else; people cite the lecture slides for this course in their papers when they use it. The field moves fast so it's a little outdated now, but this course gave me a strong and deep foundation for understanding the techniques of deep learning. I was able to apply it at work later with great success. I think this course was more worthwhile than Ng's.
rohanm93 6y ago
This list is pretty good: https://resumeworded.com/free-online-courses/ https://resumeworded.com/free-online-courses/
manca 6y ago
Machine Learning by Dr Ng is a classic. I also loved Algorithms I and II by Tim Roughgarden. Sedgewick's Algorithms are also good.
mrisoli 6y ago
I liked internet history, technology and security: https://www.coursera.org/learn/internet-history https://www.coursera.org/learn/internet-history It doesn't get very deep in terms of knowledge of networks, TCP/IP stack etc, it's a very lightweight course that's easy to get through, it was my gateway MOOCs years ago, instructor is great and there's great footage from the beginnings of the internet, it feels more like an interactive documentary than an online class.
hartem_ 6y ago
- Algorithms I and II by R. Sedgewick are great (https://www.coursera.org/instructor/~250165 https://www.coursera.org/instructor/~250165). Super easy to understand and very deep/nuanced at the same time. - Automata Theory by J. Ullman is also really good. It used to be on Coursera but is now on EdX (https://www.edx.org/course/automata-theory https://www.edx.org/course/automata-theory)
- liyanage 6y ago
  I second the recommendation for "Automata Theory", the explanations are crystal clear and I learned a lot.
  - hyperpallium2 6y ago
    I found the first part, on regular expressions really excellent (though the accelerated pace made it difficult to fully grasp all the proofs). He's a still-enthused expert. However, he didn't seem as passionate on the second part, decision languages. It's also a lot harder, yet is squeezed into even less time. To help you assess my observation: I scored in the highest segment (IIRC 95%)... After taking the course, I would say I understand the regular expressions material fully, but not decision languages. I'm still confused about showing what complexity class something is in. e.g. the complexity class of determinng two polynomials are equivalent (PIT), like x(1 + y) + y and x + (x + 1)y.
    - alisonkisk 6y ago
      Your experience aligns with how most people feel about learning about Decision Languages, based on my experience in that class in college.
anderspitman 6y ago
The UCGD bioinformatics courses are very high quality.
webreac 6y ago
I have loved https://www.coursera.org/learn/crypto https://www.coursera.org/learn/crypto? Some of the material has been very useful when I have done stripe CTF n°2.
infinyte7 6y ago
I am learning programming in C++ and found this course nice. C++ Data Structures in the STL https://www.coursera.org/projects/cpp-data-structures-in-the-stl https://www.coursera.org/projects/cpp-data-structures-in-the...
infinyte7 6y ago
Not coursera https://www.youtube.com/playlist?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b https://www.youtube.com/playlist?list=PLOtl7M3yp-DV69F32zdK7... https://www.youtube.com/playlist?list=PL462275E91FC7844D https://www.youtube.com/playlist?list=PL462275E91FC7844D
- gmiller123456 6y ago
  So people don't have to click the link to see what those are about. First link is "Alanysis of Algorithms" from Stoney Brook University, second is "Discrete Mathematics" also from Stoney Brook.
  - vidro3 6y ago
    Analysis of Algorithms is with Steven Skiena, author of Algorithm Design Manual
emmanueloga_ 6y ago
PSA: LinkGrabber exists. Get a list of URLs pointing to the recommended courses :-) [1] 1: https://chrome.google.com/webstore/detail/link-grabber/caodelkhipncidmoebgbbeemedohcdma https://chrome.google.com/webstore/detail/link-grabber/caode...
bombastry 6y ago
I took the (Penn) Calculus sequence by Robert Ghrist and really enjoyed it as a review of single variable calculus. He uses Taylor series as the basis of his explanations which I felt was really clean way to provide intuition for some of the more complicated theorems and formulae. The lecture videos have high quality animations and are broken into digestible chunks (around 10-15 minutes each). The downside is that only a few example problems are shown being worked out, but I only found this to be an issue for a few of the lectures (mainly in the applied calculus section of the course). The course also covers some interesting, non-standard topics. In particular, I liked the lecture on a discrete version of calculus (https://www.youtube.com/watch?v=NHa8UgWigZk https://www.youtube.com/watch?v=NHa8UgWigZk) which can be used to find easy solutions to series and recurrence relations (e.g. the "discrete anti-derivative" can be used to provide quick closed-form solutions to sums of the form "n^k from n=1 to K" - an example occurs at the 5:28 mark of the linked lecture, but some background from earlier in the video will be necessary to follow along). The lecture videos are available on Youtube (https://www.youtube.com/playlist?list=PLKc2XOQp0dMwj9zAXD5LlWpriIXIrGaNb https://www.youtube.com/playlist?list=PLKc2XOQp0dMwj9zAXD5Ll...), but I would recommend working through the problems on Coursera (especially the challenge problems) as well. I would also recommend that viewers watch the videos as 1.5x speed or faster. Dr. Ghrist speaks so slowly in these videos that I found it distracting. For those who have some knowledge of the standard intro calculus textbooks, the level of rigor and difficulty in this course is above the Stewart book that many universities use, but below the Spivak/Apostol/Courant type of book that an honors course may use. This used to be a single course, but Coursera split it up into 5 pieces, with somewhat unhelpful names. The sequence is "Part 1 - Functions"[1], "Part 2 - Differentiation"[2], "Part 3 - Integration"[3], "Part 4 - Applications"[4], and "Part 5 - Discrete Calculus"[5]. The first four parts names are reflected in their Coursera titles, but the "Discrete Calculus" course is titled "Single Variable Calculus" instead since it contains the final exam for the overall sequence. It's also worth mentioning that Dr. Ghrist also has other video lectures available on Youtube (https://www.youtube.com/c/ProfGhristMath https://www.youtube.com/c/ProfGhristMath) for other math courses including a sequence on multivariable calculus called "Calculus Blue." [1] https://www.coursera.org/learn/single-variable-calculus https://www.coursera.org/learn/single-variable-calculus [2] https://www.coursera.org/learn/differentiation-calculus https://www.coursera.org/learn/differentiation-calculus [3] https://www.coursera.org/learn/integration-calculus https://www.coursera.org/learn/integration-calculus [4] https://www.coursera.org/learn/applications-calculus https://www.coursera.org/learn/applications-calculus [5] https://www.coursera.org/learn/discrete-calculus https://www.coursera.org/learn/discrete-calculus
pcthrowaway 6y ago
Databases with Jennifer Widom. I think the original course I took on Stanford's platform has now been split into 3 on edx. Amazing hands-on introduction to Database concepts https://www.edx.org/course/databases-5-sql https://www.edx.org/course/databases-5-sql I quite liked the Web Development course taught by Steve Huffman (the founder of Reddit) on Udacity. It's possibly a bit dated right now.
- jamestimmins 6y ago
  +1 for Web Development with Steve Huffman. This is the course most responsible for my career as a software developer.
avmich 6y ago
I think HN should be interested by that Coursera today requires reCAPTCHA passing to log into. That filters out some browsers or extensions. Also at least some courses are paid-only - initially there were plenty of free courses. For example, even if you don't want a certificate for Deep Learning specialization, just to view videos require you to enter a credit card and agree to some dim conditions probably drafted by lawyers (and expected to be read by non-lawyers). Coursera was great initially, with well taught courses. Now it's more of a gated community, much worse IMO than it used to be. Hope there are better offerings elsewhere.
dryd 6y ago
I really enjoyed "The Modern World, Part One: Global History from 1760 to 1910" [1] by Philip Zelikow. He clearly put a lot of thought into developing his lectures -- there's also a part two [2] that picks up where the first leaves off. [1] https://www.coursera.org/learn/modern-world https://www.coursera.org/learn/modern-world [2] https://www.coursera.org/learn/modern-world-2 https://www.coursera.org/learn/modern-world-2
rognjen 6y ago
I've found courses that aren't directly related to my profession (or making money) to be the most rewarding. For example: https://www.coursera.org/learn/age-of-cathedrals https://www.coursera.org/learn/age-of-cathedrals
rskirkpatrick 6y ago
Algorithms by Princeton University, taught by Dr. Robert Sedgewick. That was the most organized and well-taught course I have taken on Coursera. The visuals for explaining algorithms were beautiful, Dr. Sedgewick explained the material extremely well, and my favorite part, were the assignments. The assignments are completed in Java and cover the lecture material from the week. For example, your 1st assignment is to use a union data structure to determine if a grid percolates, similar to a coffee filter percolating. One slight drawback with the course was that it was originally published several years ago, so the forums are not well moderates much more and some of the previous quizzes are no longer available. Also Princeton does not issue certifications of completion. Still it’s the best online course I have taken in a MOOC.
bicepjai 6y ago
This has the potential to be one of the best paid finance course online. I am working on its first course currently. This is edx version of OCW https://ocw.mit.edu/courses/sloan-school-of-management/15-401-finance-theory-i-fall-2008/ https://ocw.mit.edu/courses/sloan-school-of-management/15-40...

486 points by joshlk 6y ago

In any field that “interesting” to HN

I think Dan Grossman's Programming Languages courses are amazing if you have slept through the subject in university: https://www.coursera.org/learn/programming-languages https://www.coursera.org/learn/programming-languages

prezjordan 6y ago
+1! This is a three-parter and it was such a fun hobby for a few weeks when quarantine was kicking up. I had played with plenty of languages before but didn't realize the gaps in my knowledge. Would recommend.
Lewton 6y ago
I did this course 5+ years ago and I still remember it fondly! I can pretty confidently say that it made me a better developer
agumonkey 6y ago
I wish there was a follow up. Brown published their book online, but it's not as fun without a structure.
MattyMc 6y ago
As someone who learned to program outside of college, this course was one of my favorites.
brudgers 6y ago
I took it the second time it was offered. One of the main reasons was it was as an excuse to learn Emacs. Does anyone know if the course still encourages using Emacs?
- bagelman 6y ago
  it does!
bagelman 6y ago
Great class that really challenged me as a self-taught programmer. Rewarding assignments that pushed back the basics you often find in MOOCs
namborita 6y ago
These are absolute gems! I remember how bummed I felt watching the last video of the last course because it was ending.

joshlk 6y ago

Nand to Tetris: how a computer is built from the ground up. Starting from nand logic gates all the way to OO programming https://www.coursera.org/learn/build-a-computer https://www.coursera.org/learn/build-a-computer

Tomte 6y ago
The course is good, the book is better, in my opinion. Although it covers the same, but I like its presentation much better than the video course. Nisam/Schocken: "The Elements of Computing Systems" I have only finished the hardware part, so far, but skimming the rest I can't find Tetris anywhere. Is that really missing, although it's in the title? (I know that you can program Tetris on the machine you build in the course, but is it an exercise somewhere?
- captn3m0 6y ago
  One section asks you to learn Jack (The high-level programming language) by writing a medium-complexity program. The goal of the exercise is not to get proficient in Jack (which is a Java-like-language), but to just learn it well enough to implement the compiler. I wrote a Tic-Tac-Toe variant - but you could write anything, including Tetris.
- troupe 6y ago
  On Coursera, if I remember right, the first course gets you to the point where you have a CPU that can run machine language and an assembler. They give you an assembly version of Tetris that will run on what you built. In the second course you build the programming language that could be used to write Tetris, though I don't think you actually go through it as an exercise.
- sn9 6y ago
  The second edition of the book is actually slated for release in July. You can preorder it on Amazon.
SilasX 6y ago
Seconding this. It's the most fun I've ever had on a technical project (with the possible exception of tptacek's microcorruption.com), and really opened my eyes to all the problems you have to solve to get a working computer. Note: you can also complete all the course materials just by going to nand2tetris.org. My presentation slides promoting nand2tetris to the Austin python group: https://docs.google.com/presentation/d/1fGf2eZVOM2lHL8hFVyd2QOH-7wf0QpvVJy79gGwCScc/edit https://docs.google.com/presentation/d/1fGf2eZVOM2lHL8hFVyd2...

commonturtle 6y ago

Scott Page's Model Thinking course: https://www.coursera.org/learn/model-thinking https://www.coursera.org/learn/model-thinking. Broad overview of how to think in models to understand the world around you.

joshlk 6y ago
What does that mean to think in models?
- ayewo 6y ago
  Models are tools to help us reason clearly about the world. They help us deal with complexity in manageable chunks by focusing on salient parts of a problem, rather than the whole. From my course notes, a nearly comprehensive summary of how the social sciences use models was presented: 16 uses of modeling outside prediction include from Epstein, Joshua M. (2008). Why Model?. Journal of Artificial Societies and Social Simulation: 1. Explain (very distinct from predict) 2. Guide data collection 3. Illuminate core dynamics 4. Suggest dynamical analogies 5. Discover new questions 6. Promote a scientific habit of mind 7. Bound (bracket) outcomes to plausible ranges 8. Illuminate core uncertainties 9. Offer crisis options in near-real time 10. Demonstrate tradeoffs / suggest efficiencies 11. Challenge the robustness of prevailing theory through perturbations 12. Expose prevailing wisdom as incompatible with available data 13. Train practitioners 14. Discipline the policy dialogue 15. Educate the general public 16. Reveal the apparently simple (complex) to be complex (simple)
- alisonkisk 6y ago
  Think scientifically/mathematically. It what most people who hang out HN do intuitively, but most of the general public does not. (Like how Dr Fauci talks about COVID-19 vs how Donald Trump does).
aoshifo 6y ago
For me, this was also the most interesting course. But I don't think you can still access it (I tried a couple of months ago to revisit it). But Scott Page also has a book out on the topic "The Model Thinker", which covers most of the course.

mbaytas 6y ago

Scott Klemmer’s HCI- and design-related courses: https://www.coursera.org/instructor/~1250 https://www.coursera.org/instructor/~1250

Mimmy 6y ago

Interesting prior discussion from 2018 https://news.ycombinator.com/item?id=16745042 https://news.ycombinator.com/item?id=16745042

tsjq 6y ago
Thanks

samvher 6y ago

I quite liked "How to win a data science competition" (https://www.coursera.org/learn/competitive-data-science https://www.coursera.org/learn/competitive-data-science) where I learned a lot about validation strategies and machine learning on tabular data. The course has its own Kaggle competition. I also really liked "Discrete optimization" (https://www.coursera.org/learn/discrete-optimization https://www.coursera.org/learn/discrete-optimization). At the time that I took it it also had a competitive element where you would solve optimization problems and there was a leader board comparing all the students in the current batch. That was when courses still started in batches and were free so the experience would probably no longer be the same, unfortunately.

light_hue_1 6y ago
> I quite liked "How to win a data science competition As a machine learning researcher I am on the one hand glad that folks are learning more about the topic. On the other hand, this is totally the wrong approach and it will teach you the wrong lessons. The idea that you can just treat data as a uniform dump of tables and that grinding your way to high numbers is somehow worthwhile is simply terrible. The resulting systems won't work well in the real world and they produce horrific explanations of what is going on. This class teaches you not just the wrong tools, like boosting, it teaches you the wrong mental model. I really can't think of a worse introduction to ML than this class. Even not knowing anything would actually be better.
- samvher 6y ago
  Interesting. I definitely would not recommend this course as an only course in machine learning or indeed as an introduction, and I see where you’re coming from with the wrong mental models. I can’t be sure that I do have the right ones but I have taken a number of other courses as well and my sense is they’re ok. My main takeaway from the course was definitely not that just grinding away for higher numbers is the right thing to do (but it might be a necessary evil in a competition context). The key thing I learned here was much more about paying very close attention that your validation strategy and your testing strategy are compatible because there are many ways you can mess it up, making your models valid in-sample only. Most of the other things I had done before were also more around SVMs and neural networks and getting some experience with decision tree based algorithms was interesting.

oli5679 6y ago

I really enjoyed Tim Roughgarden's 'Algorithms' specialisation. The first half are actually on Stanford's online learning platform for free. https://www.coursera.org/specializations/algorithms https://www.coursera.org/specializations/algorithms

thecleaner 6y ago
Highly recommend this course. Good coverage of topics and the explanations help build intuition.
bhrgunatha 6y ago
I took his 2 algorithm courses on Coursera's original platform. They were stellar. In particular making practical problems that have a calculable answer that you implement yourself in whatever language you choose and check as part of the course. As opposed to having some online interpreter for some specific language. That was then hosted on Stanford's own Lagunita platform (based on the edX platform I think.) Stanford then split those 2 courses into 4 on Coursera's new platform - the same material I believe but packaged differently. Stanford then closed its Lagunita platform and those original 2 courses are now offered on edX. A similar story with Alex Aiken's excellent Compiler course and Jeffrey Ullman's Automata course too. I'm not even sure if they are still available on Coursera or not. [1] https://www.edx.org/course/algorithms-design-and-analysis https://www.edx.org/course/algorithms-design-and-analysis [2] https://www.edx.org/course/algorithms-design-and-analysis-part-2-2 https://www.edx.org/course/algorithms-design-and-analysis-pa... [3] https://www.edx.org/course/compilers https://www.edx.org/course/compilers [4] https://www.edx.org/course/automata-theory https://www.edx.org/course/automata-theory
BossingAround 6y ago
What level of math would you recommend for the courses? This is always a difficult question, because it's always "high school level math" which is rarely true. Then again, some algo courses focus highly on math and proofs while others focus more on implementation.
rskirkpatrick 6y ago
I prefer the Algorithms course by Princeton but I still really like this course. The deep dive into the mathematical proofs and timing of these algorithms is what gives this course an advantage over Princeton’s course.

etherio 6y ago

Not coursera but I'd definitely recommend Helsinki university's Elements of AI course [0]. It's quite accessible and a good introduction to artifical intelligence. [0]: https://www.elementsofai.com/ https://www.elementsofai.com/

adeel_siddiqui 6y ago

Programming Languages, Dan Grossman, UW. https://www.coursera.org/learn/programming-languages https://www.coursera.org/learn/programming-languages It is a 3 part course and a bit more intensive than other courses on Coursera with challenging assignments. It helped me gain a deeper understanding of statically vs dynamically typed languages. Designing a tiny language in Part B is the best part of the course. Concludes with a nice comparison between OOP and functional languages.

vvillena 6y ago
Did this one when it was just one single course. The content is great, but the best thing by fat is the teacher. Dan Grossman is a natural teaching talent, and this course shows how one single teacher can make a difference.
- utxaa 6y ago
  dan is awesome. nice guy too.
dzhiurgis 6y ago
Did that too and it totally changed how understand programming (was a newbie back then).
rskirkpatrick 6y ago
Thanks for the suggestion. I will check it out.

yawz 6y ago

Dr Barbara Oakley’s “Learning How to Learn” [0] is great. Edit: It gives an important understanding on how our minds function and how we learn, which, I think, forms the basis of effective work. Knowing how to work, and being an effective learner are incredibly important qualities in life. [0] https://www.coursera.org/learn/learning-how-to-learn https://www.coursera.org/learn/learning-how-to-learn

joshlk 6y ago
What’s good about it?
- thecleaner 6y ago
  You can get a sample out of her Google talk on YouTube. Basically the course tells you ideas about how to read/manage time to learn things more efficiently.
  - Ma8ee 6y ago
    And most importantly, why you should study and manage your time in certain ways. A lot of things in that course feels like it fairly obvious when you hear it, but often you might not have thought in those directions, and often it helps to get those things spelled out. If I had had that course in my early teens that would have helped me a lot.
    - thecleaner 6y ago
      I really enjoyed the part about recollecting vs rereading. This changed my perspective on how to read things. I have noticed I read less nonsense and retain more of the important topics. Also tried it with software docs. Although recollecting API names didnt help me make better software decisions but it came in handy while writing code. A bit of fluency helped reduce friction since I could code with less context switches.
      - Ma8ee 6y ago

everythingswan 6y ago

The Python for Everybody course was great. I was excited to complete it (well, the first 3 courses in the roadmap): https://www.coursera.org/specializations/python https://www.coursera.org/specializations/python As a non-programmer but a decent mather, I thought it presented the materials in a way that was easy to understand. In my mid-thirties now, I feel like I could have handled this at 18 just fine--but not in a patronizing way. It was just very clear and the professor had a good sense of humor. I just built my first time-saving Python program and it felt really satisfying. I built a few others that were cool but none actually saved me time. Very satisfying! At the end of the 3 courses (~60 hours) and some additional tinkering (~40 hours), I had the skills and that's pretty cool.

cdkee 6y ago
+1 for Dr Chuck! Echo your sentiments exactly. Had I taken this course when I was 18, I surely would have gone for a CS degree.
alisonkisk 6y ago
As someone who has been both 18 and 30, 18 is a much easier time to learn a programming language.

arcturus17 6y ago

Princeton's and Stanford's Algorithms are fantastic.

passwordreset 6y ago
I was disillusioned by Princeton's Algorithms course when I took it. I felt like I was fighting too hard with eccentricities of Java than actually learning about algorithms. In retrospect, I was wrong, because one of the things I realized that it taught me was that implementation details of algorithms are _hugely_ important, and can cause drastic differences in time and memory utilization. I can easily forget the details, but I haven't forgotten the experience of hacking out my stupid mistakes until the implementations fit the requirements.
- arcturus17 6y ago
  That was a learning for me too, but I thoroughly enjoyed the psets. I don't mind Java - setting everything up can be annoying but I find it fairly straightforward and its massive standard library comes in handy for a class like this.

kassas 6y ago

"Modern Big Data Analysis with SQL Specialization" by Cloudera is awesome. It discusses Hadoop, Hive, Impala and Big Data and the instructors are great. It is rated 4.8/5.0 https://www.coursera.org/specializations/cloudera-big-data-analysis-sql https://www.coursera.org/specializations/cloudera-big-data-a...

jschulenklopper 6y ago

https://www.classcentral.com/collection/top-free-online-courses https://www.classcentral.com/collection/top-free-online-cour... (Not just on Coursera, but also others. You can filter for the Coursera ones.)

afarzad 6y ago
Not Coursera but I really enjoyed the "Intro to Complexity" course from the Sante Fe Institute; it's highly recommended on classcentral. It gives a broad overview of how complex systems emerge from simple phenomenon and shows how cross-disciplinary some of these insights are. https://www.complexityexplorer.org/courses/104-introduction-to-complexity https://www.complexityexplorer.org/courses/104-introduction-...
9test123456789 6y ago
nb

atrisx 6y ago

Intro to Psychology: https://www.coursera.org/learn/introduction-psychology https://www.coursera.org/learn/introduction-psychology The Modern World, Part One: Global History from 1760 to 1910: https://www.coursera.org/learn/modern-world https://www.coursera.org/learn/modern-world (2nd part is as great as the first one)

maurits 6y ago

My personal favorite, Statistical Mechanics and Computations.[1]. Excelled introduction to MCMC methods, lots and lots of python programs and filmed against a green screen. Obligatory, Stanford CS231n: Convolutional Neural Networks for Visual Recognition [2] The assignments are excellent and will let you implement a deephish network from practically scratch, before diving into modern frameworks and applications. [1]: https://www.coursera.org/learn/statistical-mechanics https://www.coursera.org/learn/statistical-mechanics [2]: http://cs231n.stanford.edu/index.html http://cs231n.stanford.edu/index.html

Tepix 6y ago

I thought "The science of the solar system" by Mike Brown was an excellent introduction. https://www.coursera.org/learn/solar-system https://www.coursera.org/learn/solar-system

vvm 6y ago
I second this, one of the best courses I attended on coursera.

krtkush 6y ago

Model Thinking by Scott E. Page - https://www.coursera.org/learn/model-thinking/home/welcome https://www.coursera.org/learn/model-thinking/home/welcome

joshlk 6y ago

Has anyone tried either?: - "Fundamentals of Parallelism on Intel Architecture" https://www.coursera.org/learn/parallelism-ia https://www.coursera.org/learn/parallelism-ia - "Introduction to High-Performance and Parallel Computing" https://www.coursera.org/learn/introduction-high-performance-computing https://www.coursera.org/learn/introduction-high-performance...

dimmuborgir 6y ago

Audio Signal Processing for Music Applications Professor Xavier Serra[1] is a highly respected veteran in the field. [1] https://en.m.wikipedia.org/wiki/Xavier_Serra https://en.m.wikipedia.org/wiki/Xavier_Serra

mportela 6y ago

Another thread from earlier this year with pretty good recommendations: https://news.ycombinator.com/item?id=22826722 https://news.ycombinator.com/item?id=22826722

rajbiswas125 6y ago

Andrew NG Deep Learning courses were nice, especially for an absolute beginner.

iou 6y ago

Cryptography 1, time well spent. ~3000 reviews at 4.8 stars https://www.coursera.org/learn/crypto https://www.coursera.org/learn/crypto

GekkePrutser 6y ago
+1 for this... Really good. Did it years ago and it was all very clear to me. However as I don't use this in daily life I pretty much lost all the knowledge again :)
- stockkid 6y ago
  Same. Having finished the course years ago, I remember most vividly the following: never implement your own crypto. Not many details survived the time but it was intellectually rewarding.
verroq 6y ago
Just don’t hold your breath for Cryptography 2
- latenightcoding 6y ago
  I was hoping it would finally be available this year. Now I think it's never going to happen.
  - Thorentis 6y ago
    The course is apparently being released when the accompanying book is complete. The book is free, and you can see the current version here: https://cryptobook.us/ https://cryptobook.us/
    - iou 6y ago
      It's super dense though, even with a math background I struggled to make headway.
- 6y ago

Nowado 6y ago

I have no idea how 'Machine Learning' from Ng is not mentioned. It's fine in teaching you introductory (although it seems to cover more basics than a lot of other courses do, somehow) ML. But more importantly, it's a well designed course. You can see how each piece uses previous pieces and how it solves problems and edge cases not covered earlier.

iou 6y ago
Yes!! Though I did it a long time ago and I'm not sure if it's been modernised for current ML norms?
- Nowado 6y ago
  AFAIK it wasn't. Ng just makes new courses for new methods. That said, I'm yet to see better coverage of that topics (If someone knows, I'd really like to get them. I forget pieces every now and then, and having more efficient refresh method is always welcome).
  - visarga 6y ago
    I hope everyone was referring to Andrew's blackboard course: https://www.youtube.com/watch?v=UzxYlbK2c7E&list=PLA89DCFA6ADACE599 https://www.youtube.com/watch?v=UzxYlbK2c7E&list=PLA89DCFA6A... instead of the one that started Coursera: https://www.youtube.com/watch?v=PPLop4L2eGk&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN https://www.youtube.com/watch?v=PPLop4L2eGk&list=PLLssT5z_Ds...
omarhaneef 6y ago
I appreciate his attention to pedagogy. Even small things like noticing that students learn better with Matlab/Octave than with R or Python is the kind of observation that takes a combination of knowledge, effort and caring about teaching.
- BoiledCabbage 6y ago
  I could be wrong, but I think it has nothing to do with that, and now to do with the course being so old that R and Python weren't the standard ML languages yet.

veganjay 6y ago

I can think of many - I have taken several starting since 2013. The tricky thing is that Coursera classes seem to get merged, re-mashed or otherwise re-branded. And as such only one currently is listed in my "Completed" courses section of my profile. Having said that and with the caveat that these probably changed since I taken them, I recommend the following: - Cryptography - https://www.coursera.org/learn/crypto https://www.coursera.org/learn/crypto - great introduction to the fundamentals and math behind cryptography. A lot of theory but also some practical exercises. This is my top recommended. - Machine Learning - https://www.coursera.org/learn/machine-learning https://www.coursera.org/learn/machine-learning - a good introduction to the basic of machine learning; focuses on octave/matlab and does not dive into frameworks like scikitlearn or tensorflow - Introduction to Interactive Programming with Python - https://www.coursera.org/learn/interactive-python-1 https://www.coursera.org/learn/interactive-python-1 - I took a course from Rice University on Python programming through making games that was fun. As far as I can tell, this is the modern incarnation in two parts. - Software Security - https://www.coursera.org/learn/software-security https://www.coursera.org/learn/software-security - goes into stack / overflow exploits, tools for testing, and web-based attacks - Functional Programming Principles in Scala - https://www.coursera.org/specializations/scala https://www.coursera.org/specializations/scala - this was a good introduction to scala and functional programming - it got me thinking in a different way - C++ for C Programmers - https://www.coursera.org/learn/c-plus-plus-a https://www.coursera.org/learn/c-plus-plus-a - I think this was the first coursera class I took. This course dove into the C++ STL and a lot of modern features introduced in C++11.

mlinksva 6y ago
> as such only one currently is listed in my "Completed" courses section of my profile. That's surprising to me: wouldn't Coursera want learners to be reassured that whatever signalling benefit there is to completing a course will remain forever? I took a few courses in 2013 just to see what MOOCs are really like and completed two (Programming Languages, as taken by many here, and Introduction to Mathematical Thinking, which IIRC was mostly about logic) which indeed are not listed under "completed" in my profile. I found them at https://www.coursera.org/accomplishments https://www.coursera.org/accomplishments though.

ra7 6y ago

Economics of Money and Banking by Perry Mehrling - https://www.coursera.org/learn/money-banking https://www.coursera.org/learn/money-banking Great course to learn about monetary systems, central banks and its effects on financial markets.

repsilat 6y ago

I took a bunch back in the day, and I liked Economics of Money and Banking[1] (by Perry Mehrling) more than most other courses. It's partly a history of the American financial system, and partly a tour of some modern financial instruments and institutions. The focus is on how things work and why they're designed as they are, and not so much on how things are priced. Deposits, bonds, commodity futures, central banks, how it all fits together, what purpose it all serves -- how it's not just gambling or an abstract game used to extract money from the productive economy. One of the stated aims of the course is to get you in a position where you can read the Financial Times without going cross-eyed, and it works really well to give a clarifying framework for understanding market concepts outside the course's scope. Another I really liked was "The Modern and the Postmodern" by Michael Roth. I don't know if that course would work well "at your own pace" though, the reading and peer essay feedback was a big part of it. 1: https://www.coursera.org/learn/money-banking https://www.coursera.org/learn/money-banking

littlestymaar 6y ago
I came here to recommend the same course. It's really well done and covers not only conventional banking but also covers quantitative easing post financial crisis. And the guy is also pretty funny.
avyfain 6y ago
I did "The Modern and the Postmodern" last year, and really enjoyed it without doing the essays/peer review. Curiously I'm now working through Mehrling's course, too. Another one I'd recommend if you enjoyed those two, although in a very different vein is Bloom's Moralities of Everyday Life, which is supposedly a psychology course, but really goes into comparative culture questions that IMO make it closer to an anthropology course. https://www.coursera.org/learn/moralities https://www.coursera.org/learn/moralities

davuinci 6y ago

Financial Markets course [0] taught by Robert Shiller (Nobel laureate) is a phenomenal course to understand the basics of financial markets. He explains how financial markets work from an engineering perspective which is an interesting approach in contrast to other similar courses. [0] https://www.coursera.org/learn/financial-markets-global https://www.coursera.org/learn/financial-markets-global

closeparen 6y ago
I tried this course and found it nearly unwatchable due to the editing. Rapid cuts jump around topics and rooms and days without any transitions and without any logical continuity either. Shiller frequently references things he probably said 5 minutes ago in the actual lecture, but won’t say for 10 more videos in the Coursera edit. I cannot find anyone else talking about this in the reviews; they are all glowing. Wondering if I’m crazy, if Coursera is glitching just for me, or if no one actually watched the videos.
- soramimo 6y ago
  Here's the 2011 version of Shiller's lecture on Financial Markets on YouTube, which doesn't have this problem: https://www.youtube.com/playlist?list=PL8FB14A2200B87185 https://www.youtube.com/playlist?list=PL8FB14A2200B87185
  - closeparen 6y ago
    Thank you!

abecedarius 6y ago

I quite enjoyed https://www.udacity.com/course/design-of-computer-programs--cs212 https://www.udacity.com/course/design-of-computer-programs--... -- program design by Peter Norvig. (Disclaimer: I had a very small part in preparing it.)

hiyer 6y ago
+1 for this. It's quite python-specific, but I found it amazingly insightful.

elil17 6y ago

The Science of Well Being. A great course about how psychologists research human happiness and what the current state of the art suggests are the best strategies for leading a fulfilling life. https://www.coursera.org/learn/the-science-of-well-being https://www.coursera.org/learn/the-science-of-well-being

omarhaneef 6y ago

I should mention that they have a Black Friday or cyber Monday type special right now where you take a course or a month for free.

moxylush 6y ago

Thanks for the info about Machine Learning from Ng. I've been trying to find that course.

danr4 6y ago

"Introduction to Public Speaking" - Dr. Matt McGarrity I think public speaking is a very important skill that not enough people take the time to learn.

gmiller123456 6y ago

Differential Equations in Action https://www.udacity.com/course/differential-equations-in-action--cs222 https://www.udacity.com/course/differential-equations-in-act... It's not an intense differential equations course, and I don't think you even need calculus to understand or complete the exercises. It has a lot of really great, well, explained, fun exercises like computing a gravitational slingshot, computing the spread of an epidemic, then N-body problem, and others. The exercises are solved programmatically, not with math equations. America's Unwritten Constitution https://www.coursera.org/learn/unwritten-constitution https://www.coursera.org/learn/unwritten-constitution America's Written Constitution https://www.coursera.org/learn/written-constitution https://www.coursera.org/learn/written-constitution If you're American, you'll likely find both of these courses extremely interesting. What they (probably) taught you in grade/high school was very overly simplified, or just wrong. This is geared toward people who have no background in law. I don't remember there being amazing exercises to do, but there were a lot of mind blowing facts I learned about things the constitution does and doesn't cover.

x87678r 6y ago

This thread is great. I've already enrolled and given up on 20ish courses, now I have another 4 enrolled. :)

albertzeyer 6y ago

I very much enjoyed Geoffrey Hinton's course about Neural Networks. But I cannot find it anymore on Coursera? Anyway, I found it here: https://www.youtube.com/playlist?list=PLoRl3Ht4JOcdU872GhiYWf6jwrk_SNhz9 https://www.youtube.com/playlist?list=PLoRl3Ht4JOcdU872GhiYW...

modeless 6y ago
Surprised this isn't higher. It was absolutely incredible at the time. It was cutting edge: the now well known optimizer RMSProp was presented by Hinton in this course and not even published anywhere else; people cite the lecture slides for this course in their papers when they use it. The field moves fast so it's a little outdated now, but this course gave me a strong and deep foundation for understanding the techniques of deep learning. I was able to apply it at work later with great success. I think this course was more worthwhile than Ng's.

rohanm93 6y ago

This list is pretty good: https://resumeworded.com/free-online-courses/ https://resumeworded.com/free-online-courses/

manca 6y ago

Machine Learning by Dr Ng is a classic. I also loved Algorithms I and II by Tim Roughgarden. Sedgewick's Algorithms are also good.

mrisoli 6y ago

I liked internet history, technology and security: https://www.coursera.org/learn/internet-history https://www.coursera.org/learn/internet-history It doesn't get very deep in terms of knowledge of networks, TCP/IP stack etc, it's a very lightweight course that's easy to get through, it was my gateway MOOCs years ago, instructor is great and there's great footage from the beginnings of the internet, it feels more like an interactive documentary than an online class.

hartem_ 6y ago

- Algorithms I and II by R. Sedgewick are great (https://www.coursera.org/instructor/~250165 https://www.coursera.org/instructor/~250165). Super easy to understand and very deep/nuanced at the same time. - Automata Theory by J. Ullman is also really good. It used to be on Coursera but is now on EdX (https://www.edx.org/course/automata-theory https://www.edx.org/course/automata-theory)

liyanage 6y ago
I second the recommendation for "Automata Theory", the explanations are crystal clear and I learned a lot.
- hyperpallium2 6y ago
  I found the first part, on regular expressions really excellent (though the accelerated pace made it difficult to fully grasp all the proofs). He's a still-enthused expert. However, he didn't seem as passionate on the second part, decision languages. It's also a lot harder, yet is squeezed into even less time. To help you assess my observation: I scored in the highest segment (IIRC 95%)... After taking the course, I would say I understand the regular expressions material fully, but not decision languages. I'm still confused about showing what complexity class something is in. e.g. the complexity class of determinng two polynomials are equivalent (PIT), like x(1 + y) + y and x + (x + 1)y.
  - alisonkisk 6y ago
    Your experience aligns with how most people feel about learning about Decision Languages, based on my experience in that class in college.

anderspitman 6y ago

The UCGD bioinformatics courses are very high quality.

webreac 6y ago

I have loved https://www.coursera.org/learn/crypto https://www.coursera.org/learn/crypto? Some of the material has been very useful when I have done stripe CTF n°2.

infinyte7 6y ago

I am learning programming in C++ and found this course nice. C++ Data Structures in the STL https://www.coursera.org/projects/cpp-data-structures-in-the-stl https://www.coursera.org/projects/cpp-data-structures-in-the...

infinyte7 6y ago

Not coursera https://www.youtube.com/playlist?list=PLOtl7M3yp-DV69F32zdK7YJcNXpTunF2b https://www.youtube.com/playlist?list=PLOtl7M3yp-DV69F32zdK7... https://www.youtube.com/playlist?list=PL462275E91FC7844D https://www.youtube.com/playlist?list=PL462275E91FC7844D

gmiller123456 6y ago
So people don't have to click the link to see what those are about. First link is "Alanysis of Algorithms" from Stoney Brook University, second is "Discrete Mathematics" also from Stoney Brook.
- vidro3 6y ago
  Analysis of Algorithms is with Steven Skiena, author of Algorithm Design Manual

emmanueloga_ 6y ago

PSA: LinkGrabber exists. Get a list of URLs pointing to the recommended courses :-) [1] 1: https://chrome.google.com/webstore/detail/link-grabber/caodelkhipncidmoebgbbeemedohcdma https://chrome.google.com/webstore/detail/link-grabber/caode...

bombastry 6y ago

I took the (Penn) Calculus sequence by Robert Ghrist and really enjoyed it as a review of single variable calculus. He uses Taylor series as the basis of his explanations which I felt was really clean way to provide intuition for some of the more complicated theorems and formulae. The lecture videos have high quality animations and are broken into digestible chunks (around 10-15 minutes each). The downside is that only a few example problems are shown being worked out, but I only found this to be an issue for a few of the lectures (mainly in the applied calculus section of the course). The course also covers some interesting, non-standard topics. In particular, I liked the lecture on a discrete version of calculus (https://www.youtube.com/watch?v=NHa8UgWigZk https://www.youtube.com/watch?v=NHa8UgWigZk) which can be used to find easy solutions to series and recurrence relations (e.g. the "discrete anti-derivative" can be used to provide quick closed-form solutions to sums of the form "n^k from n=1 to K" - an example occurs at the 5:28 mark of the linked lecture, but some background from earlier in the video will be necessary to follow along). The lecture videos are available on Youtube (https://www.youtube.com/playlist?list=PLKc2XOQp0dMwj9zAXD5LlWpriIXIrGaNb https://www.youtube.com/playlist?list=PLKc2XOQp0dMwj9zAXD5Ll...), but I would recommend working through the problems on Coursera (especially the challenge problems) as well. I would also recommend that viewers watch the videos as 1.5x speed or faster. Dr. Ghrist speaks so slowly in these videos that I found it distracting. For those who have some knowledge of the standard intro calculus textbooks, the level of rigor and difficulty in this course is above the Stewart book that many universities use, but below the Spivak/Apostol/Courant type of book that an honors course may use. This used to be a single course, but Coursera split it up into 5 pieces, with somewhat unhelpful names. The sequence is "Part 1 - Functions"[1], "Part 2 - Differentiation"[2], "Part 3 - Integration"[3], "Part 4 - Applications"[4], and "Part 5 - Discrete Calculus"[5]. The first four parts names are reflected in their Coursera titles, but the "Discrete Calculus" course is titled "Single Variable Calculus" instead since it contains the final exam for the overall sequence. It's also worth mentioning that Dr. Ghrist also has other video lectures available on Youtube (https://www.youtube.com/c/ProfGhristMath https://www.youtube.com/c/ProfGhristMath) for other math courses including a sequence on multivariable calculus called "Calculus Blue." [1] https://www.coursera.org/learn/single-variable-calculus https://www.coursera.org/learn/single-variable-calculus [2] https://www.coursera.org/learn/differentiation-calculus https://www.coursera.org/learn/differentiation-calculus [3] https://www.coursera.org/learn/integration-calculus https://www.coursera.org/learn/integration-calculus [4] https://www.coursera.org/learn/applications-calculus https://www.coursera.org/learn/applications-calculus [5] https://www.coursera.org/learn/discrete-calculus https://www.coursera.org/learn/discrete-calculus

pcthrowaway 6y ago

Databases with Jennifer Widom. I think the original course I took on Stanford's platform has now been split into 3 on edx. Amazing hands-on introduction to Database concepts https://www.edx.org/course/databases-5-sql https://www.edx.org/course/databases-5-sql I quite liked the Web Development course taught by Steve Huffman (the founder of Reddit) on Udacity. It's possibly a bit dated right now.

jamestimmins 6y ago
+1 for Web Development with Steve Huffman. This is the course most responsible for my career as a software developer.

avmich 6y ago

I think HN should be interested by that Coursera today requires reCAPTCHA passing to log into. That filters out some browsers or extensions. Also at least some courses are paid-only - initially there were plenty of free courses. For example, even if you don't want a certificate for Deep Learning specialization, just to view videos require you to enter a credit card and agree to some dim conditions probably drafted by lawyers (and expected to be read by non-lawyers). Coursera was great initially, with well taught courses. Now it's more of a gated community, much worse IMO than it used to be. Hope there are better offerings elsewhere.

dryd 6y ago

I really enjoyed "The Modern World, Part One: Global History from 1760 to 1910" [1] by Philip Zelikow. He clearly put a lot of thought into developing his lectures -- there's also a part two [2] that picks up where the first leaves off. [1] https://www.coursera.org/learn/modern-world https://www.coursera.org/learn/modern-world [2] https://www.coursera.org/learn/modern-world-2 https://www.coursera.org/learn/modern-world-2

rognjen 6y ago

I've found courses that aren't directly related to my profession (or making money) to be the most rewarding. For example: https://www.coursera.org/learn/age-of-cathedrals https://www.coursera.org/learn/age-of-cathedrals

rskirkpatrick 6y ago

Algorithms by Princeton University, taught by Dr. Robert Sedgewick. That was the most organized and well-taught course I have taken on Coursera. The visuals for explaining algorithms were beautiful, Dr. Sedgewick explained the material extremely well, and my favorite part, were the assignments. The assignments are completed in Java and cover the lecture material from the week. For example, your 1st assignment is to use a union data structure to determine if a grid percolates, similar to a coffee filter percolating. One slight drawback with the course was that it was originally published several years ago, so the forums are not well moderates much more and some of the previous quizzes are no longer available. Also Princeton does not issue certifications of completion. Still it’s the best online course I have taken in a MOOC.

bicepjai 6y ago

This has the potential to be one of the best paid finance course online. I am working on its first course currently. This is edx version of OCW https://ocw.mit.edu/courses/sloan-school-of-management/15-401-finance-theory-i-fall-2008/ https://ocw.mit.edu/courses/sloan-school-of-management/15-40...