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Ask HN: Top Coursera Courses?

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Re: Ask HN: Top Coursera Courses?

#111

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

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. Won…

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

Re: Ask HN: Top Coursera Courses?

#112
post #95

- Algorithms I and II by R. Sedgewick are great ( 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 )

I second the recommendation for "Automata Theory", the explanations are crystal clear and I learned a lot.

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.

Re: Ask HN: Top Coursera Courses?

#113
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

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.

Re: Ask HN: Top Coursera Courses?

#114

Earlier quoted context omitted.

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. Won…

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

Thank you!

Re: Ask HN: Top Coursera Courses?

#115
post #41

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.

This was the first course I did on Coursera and it is by far the best introductary course for machine learning I have ever seen, but my sample size is pretty small ;)

I agree it's the best out there from the few that I've see that gives you fantastic intuition into what's going on. I see it as the best "invitation-to-further-exploration" available.

Re: Ask HN: Top Coursera Courses?

#116

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=PLoRl3Ht4JOcdU872GhiYW...

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.

Re: Ask HN: Top Coursera Courses?

#117

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 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.

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

Re: Ask HN: Top Coursera Courses?

#119
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) 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=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) for other math courses including a sequence on multivariable calculus called "Calculus Blue."

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

[2] https://www.coursera.org/learn/differentiation-calculus

[3] https://www.coursera.org/learn/integration-calculus

[4] https://www.coursera.org/learn/applications-calculus

[5] https://www.coursera.org/learn/discrete-calculus

Re: Ask HN: Top Coursera Courses?

#120

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 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…

+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.

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