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.<p>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.<p>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.<p>1: <a href="https://www.coursera.org/learn/money-banking" rel="nofollow">https://www.coursera.org/learn/money-banking</a>
I have no idea how 'Machine Learning' from Ng is not mentioned.<p>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.
Programming Languages, Dan Grossman, UW.
<a href="https://www.coursera.org/learn/programming-languages" rel="nofollow">https://www.coursera.org/learn/programming-languages</a>
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.
Dr Barbara Oakley’s “Learning How to Learn” [0] is great.<p>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.<p>[0] <a href="https://www.coursera.org/learn/learning-how-to-learn" rel="nofollow">https://www.coursera.org/learn/learning-how-to-learn</a>
I think Dan Grossman's Programming Languages courses are amazing if you have slept through the subject in university: <a href="https://www.coursera.org/learn/programming-languages" rel="nofollow">https://www.coursera.org/learn/programming-languages</a>
Nand to Tetris: how a computer is built from the ground up. Starting from nand logic gates all the way to OO programming<p><a href="https://www.coursera.org/learn/build-a-computer" rel="nofollow">https://www.coursera.org/learn/build-a-computer</a>
Differential Equations in Action
<a href="https://www.udacity.com/course/differential-equations-in-action--cs222" rel="nofollow">https://www.udacity.com/course/differential-equations-in-act...</a><p>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.<p>America's Unwritten Constitution
<a href="https://www.coursera.org/learn/unwritten-constitution" rel="nofollow">https://www.coursera.org/learn/unwritten-constitution</a>
America's Written Constitution
<a href="https://www.coursera.org/learn/written-constitution" rel="nofollow">https://www.coursera.org/learn/written-constitution</a><p>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.
I really enjoyed Tim Roughgarden's 'Algorithms' specialisation. The first half are actually on Stanford's online learning platform for free.<p><a href="https://www.coursera.org/specializations/algorithms" rel="nofollow">https://www.coursera.org/specializations/algorithms</a>
I quite liked "How to win a data science competition" (<a href="https://www.coursera.org/learn/competitive-data-science" rel="nofollow">https://www.coursera.org/learn/competitive-data-science</a>) where I learned a lot about validation strategies and machine learning on tabular data. The course has its own Kaggle competition.<p>I also really liked "Discrete optimization" (<a href="https://www.coursera.org/learn/discrete-optimization" rel="nofollow">https://www.coursera.org/learn/discrete-optimization</a>). 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.
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.<p>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.<p>[1]: <a href="https://www.coursera.org/learn/statistical-mechanics" rel="nofollow">https://www.coursera.org/learn/statistical-mechanics</a>
[2]: <a href="http://cs231n.stanford.edu/index.html" rel="nofollow">http://cs231n.stanford.edu/index.html</a>
Cryptography 1, time well spent. ~3000 reviews at 4.8 stars<p><a href="https://www.coursera.org/learn/crypto" rel="nofollow">https://www.coursera.org/learn/crypto</a>
The Python for Everybody course was great. I was excited to complete it (well, the first 3 courses in the roadmap): <a href="https://www.coursera.org/specializations/python" rel="nofollow">https://www.coursera.org/specializations/python</a><p>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.<p>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.
I quite enjoyed <a href="https://www.udacity.com/course/design-of-computer-programs--cs212" rel="nofollow">https://www.udacity.com/course/design-of-computer-programs--...</a> -- program design by Peter Norvig. (Disclaimer: I had a very small part in preparing it.)
Scott Page's Model Thinking course: <a href="https://www.coursera.org/learn/model-thinking" rel="nofollow">https://www.coursera.org/learn/model-thinking</a>. Broad overview of how to think in models to understand the world around you.
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.<p>[0] <a href="https://www.coursera.org/learn/financial-markets-global" rel="nofollow">https://www.coursera.org/learn/financial-markets-global</a>
Has anyone tried either?:
- "Fundamentals of Parallelism on Intel Architecture" <a href="https://www.coursera.org/learn/parallelism-ia" rel="nofollow">https://www.coursera.org/learn/parallelism-ia</a>
- "Introduction to High-Performance and Parallel Computing" <a href="https://www.coursera.org/learn/introduction-high-performance-computing" rel="nofollow">https://www.coursera.org/learn/introduction-high-performance...</a>
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.<p>Having said that and with the caveat that these probably changed since I taken them, I recommend the following:<p>- Cryptography - <a href="https://www.coursera.org/learn/crypto" rel="nofollow">https://www.coursera.org/learn/crypto</a> - great introduction to the fundamentals and math behind cryptography. A lot of theory but also some practical exercises. This is my top recommended.<p>- Machine Learning - <a href="https://www.coursera.org/learn/machine-learning" rel="nofollow">https://www.coursera.org/learn/machine-learning</a> - a good introduction to the basic of machine learning; focuses on octave/matlab and does not dive into frameworks like scikitlearn or tensorflow<p>- Introduction to Interactive Programming with Python - <a href="https://www.coursera.org/learn/interactive-python-1" rel="nofollow">https://www.coursera.org/learn/interactive-python-1</a> -
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.<p>- Software Security - <a href="https://www.coursera.org/learn/software-security" rel="nofollow">https://www.coursera.org/learn/software-security</a> - goes into stack / overflow exploits, tools for testing, and web-based attacks<p>- Functional Programming Principles in Scala - <a href="https://www.coursera.org/specializations/scala" rel="nofollow">https://www.coursera.org/specializations/scala</a> - this was a good introduction to scala and functional programming - it got me thinking in a different way<p>- C++ for C Programmers - <a href="https://www.coursera.org/learn/c-plus-plus-a" rel="nofollow">https://www.coursera.org/learn/c-plus-plus-a</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.
I very much enjoyed Geoffrey Hinton's course about Neural Networks. But I cannot find it anymore on Coursera?<p>Anyway, I found it here: <a href="https://www.youtube.com/playlist?list=PLoRl3Ht4JOcdU872GhiYWf6jwrk_SNhz9" rel="nofollow">https://www.youtube.com/playlist?list=PLoRl3Ht4JOcdU872GhiYW...</a>
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.<p>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.<p>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.<p>Still it’s the best online course I have taken in a MOOC.
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.<p><a href="https://www.coursera.org/learn/the-science-of-well-being" rel="nofollow">https://www.coursera.org/learn/the-science-of-well-being</a>
Intro to Psychology: <a href="https://www.coursera.org/learn/introduction-psychology" rel="nofollow">https://www.coursera.org/learn/introduction-psychology</a><p>The Modern World, Part One: Global History from 1760 to 1910: <a href="https://www.coursera.org/learn/modern-world" rel="nofollow">https://www.coursera.org/learn/modern-world</a> (2nd part is as great as the first one)
I think HN should be interested by that Coursera today requires reCAPTCHA passing to log into. That filters out some browsers or extensions.<p>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).<p>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.
Not coursera but I'd definitely recommend Helsinki university's Elements of AI course [0].<p>It's quite accessible and a good introduction to artifical intelligence.<p>[0]: <a href="https://www.elementsofai.com/" rel="nofollow">https://www.elementsofai.com/</a>
- Algorithms I and II by R. Sedgewick are great (<a href="https://www.coursera.org/instructor/~250165" rel="nofollow">https://www.coursera.org/instructor/~250165</a>). Super easy to understand and very deep/nuanced at the same time.<p>- Automata Theory by J. Ullman is also really good. It used to be on Coursera but is now on EdX (<a href="https://www.edx.org/course/automata-theory" rel="nofollow">https://www.edx.org/course/automata-theory</a>)
Another thread from earlier this year with pretty good recommendations: <a href="https://news.ycombinator.com/item?id=22826722" rel="nofollow">https://news.ycombinator.com/item?id=22826722</a>
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.<p>[1] <a href="https://www.coursera.org/learn/modern-world" rel="nofollow">https://www.coursera.org/learn/modern-world</a><p>[2] <a href="https://www.coursera.org/learn/modern-world-2" rel="nofollow">https://www.coursera.org/learn/modern-world-2</a>
"Introduction to Public Speaking" - Dr. Matt McGarrity<p>I think public speaking is a very important skill that not enough people take the time to learn.
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 <a href="https://ocw.mit.edu/courses/sloan-school-of-management/15-401-finance-theory-i-fall-2008/" rel="nofollow">https://ocw.mit.edu/courses/sloan-school-of-management/15-40...</a>
Model Thinking by Scott E. Page - <a href="https://www.coursera.org/learn/model-thinking/home/welcome" rel="nofollow">https://www.coursera.org/learn/model-thinking/home/welcome</a>
I thought "The science of the solar system" by Mike Brown was an excellent introduction.<p><a href="https://www.coursera.org/learn/solar-system" rel="nofollow">https://www.coursera.org/learn/solar-system</a>
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 <a href="https://www.edx.org/course/databases-5-sql" rel="nofollow">https://www.edx.org/course/databases-5-sql</a><p>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.
"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<p><a href="https://www.coursera.org/specializations/cloudera-big-data-analysis-sql" rel="nofollow">https://www.coursera.org/specializations/cloudera-big-data-a...</a>
PSA: LinkGrabber exists. Get a list of URLs pointing to the recommended courses :-) [1]<p>1: <a href="https://chrome.google.com/webstore/detail/link-grabber/caodelkhipncidmoebgbbeemedohcdma" rel="nofollow">https://chrome.google.com/webstore/detail/link-grabber/caode...</a>
Audio Signal Processing for Music Applications<p>Professor Xavier Serra[1] is a highly respected veteran in the field.<p>[1] <a href="https://en.m.wikipedia.org/wiki/Xavier_Serra" rel="nofollow">https://en.m.wikipedia.org/wiki/Xavier_Serra</a>
I have loved <a href="https://www.coursera.org/learn/crypto" rel="nofollow">https://www.coursera.org/learn/crypto</a>? Some of the material has been very useful when I have done stripe CTF n°2.
I liked internet history, technology and security: <a href="https://www.coursera.org/learn/internet-history" rel="nofollow">https://www.coursera.org/learn/internet-history</a><p>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.
Scott Klemmer’s HCI- and design-related courses: <a href="https://www.coursera.org/instructor/~1250" rel="nofollow">https://www.coursera.org/instructor/~1250</a>
This list is pretty good: <a href="https://resumeworded.com/free-online-courses/" rel="nofollow">https://resumeworded.com/free-online-courses/</a>
I've found courses that aren't directly related to my profession (or making money) to be the most rewarding. For example: <a href="https://www.coursera.org/learn/age-of-cathedrals" rel="nofollow">https://www.coursera.org/learn/age-of-cathedrals</a>
I am learning programming in C++ and found this course nice.
C++ Data Structures in the STL
<a href="https://www.coursera.org/projects/cpp-data-structures-in-the-stl" rel="nofollow">https://www.coursera.org/projects/cpp-data-structures-in-the...</a>
Economics of Money and Banking by Perry Mehrling - <a href="https://www.coursera.org/learn/money-banking" rel="nofollow">https://www.coursera.org/learn/money-banking</a><p>Great course to learn about monetary systems, central banks and its effects on financial markets.
<a href="https://www.classcentral.com/collection/top-free-online-courses" rel="nofollow">https://www.classcentral.com/collection/top-free-online-cour...</a><p>(Not just on Coursera, but also others. You can filter for the Coursera ones.)
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).<p>The course also covers some interesting, non-standard topics. In particular, I liked the lecture on a discrete version of calculus (<a href="https://www.youtube.com/watch?v=NHa8UgWigZk" rel="nofollow">https://www.youtube.com/watch?v=NHa8UgWigZk</a>) 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).<p>The lecture videos are available on Youtube (<a href="https://www.youtube.com/playlist?list=PLKc2XOQp0dMwj9zAXD5LlWpriIXIrGaNb" rel="nofollow">https://www.youtube.com/playlist?list=PLKc2XOQp0dMwj9zAXD5Ll...</a>), 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.<p>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.<p>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.<p>It's also worth mentioning that Dr. Ghrist also has other video lectures available on Youtube (<a href="https://www.youtube.com/c/ProfGhristMath" rel="nofollow">https://www.youtube.com/c/ProfGhristMath</a>) for other math courses including a sequence on multivariable calculus called "Calculus Blue."<p>[1] <a href="https://www.coursera.org/learn/single-variable-calculus" rel="nofollow">https://www.coursera.org/learn/single-variable-calculus</a><p>[2] <a href="https://www.coursera.org/learn/differentiation-calculus" rel="nofollow">https://www.coursera.org/learn/differentiation-calculus</a><p>[3] <a href="https://www.coursera.org/learn/integration-calculus" rel="nofollow">https://www.coursera.org/learn/integration-calculus</a><p>[4] <a href="https://www.coursera.org/learn/applications-calculus" rel="nofollow">https://www.coursera.org/learn/applications-calculus</a><p>[5] <a href="https://www.coursera.org/learn/discrete-calculus" rel="nofollow">https://www.coursera.org/learn/discrete-calculus</a>