Ask HN: What were some good MOOCs you participated in in 2013? | Hacker News Reader

Ask HN: What were some good MOOCs you participated in in 2013?

5 pointschl11 comments

All in all, Eric Lander's 7.00x (Introduction to Biology) probably was the best of all the courses I completed in 2013. Lander is a fantastic lecturer -- it wasn't uncommon that his lectures (or shall I say performances) ended in applause.

Going beyond "just" videos and multiple-choice quizzes, the MITx folks built/assembled an impressive array of mostly web-based tools (e.g. a 3D molecule viewer, a molecule editor, a simplified version of genome viewers used by actual biologists) to support the learning enterprise.

Here's a glowing review that (unlike my scribblings here) starts to do the 7.00x experience justice: http://okazakifragments.wordpress.com/2013/05/29/the-best-mo...

I really enjoyed Programming Languages by Dan Grossman (U. Washington) on Coursera. Well organised course, smoothly run. https://class.coursera.org/proglang-002

Machine Learning. I thought it was a really tough class and took more time than they say (they say workload: 5-7 hours/week -- maybe if you are perfect and your code never has bugs that you need to spend time debugging -- the course is based on programming assignments in Octave where you have to demonstrate mastery of machine learning concepts), but I put in a lot of extra time, mastered everything, finished with a 100. Andrew Ng is a top-notch teacher, even though his speaking style is very low-key. https://www.coursera.org/course/ml

I finally made time for "Functional Programming in Scala" and it was fun.

However, I must add that when I tried to use Scala in the real-world, it was considerably more complicated due to implicits, CanBuildFrom, and other "invisible hands" (not merely synactic sugar, mind you).

Learning Creative Learning: http://learn.media.mit.edu (for as long as they keep the site up anyway)

Introduced me to some new ideas about learning, and solidified some ambiguous thoughts I already had. Much fun.

Maps and the Geospatial Revolution on Coursera

Intro to Machine Learning on Coursera was pretty great, just the right level of difficulty for a novice high schooler.

I'm a high schooler. My knowledge is mainly in the front-end realm, with the vast majority of 'programming' I do being in JavaScript. Do you think I would be able to take it successfully?

Im a beginner um programming, and did machine learning course right after a introdutory course (CS50 and 6.00x at Edx).

I've been able to do the whole course, but only because i have good math skills. My impression is that math skills (calculus and linear algebra) are much more needed than coding skills in this course.

Im currently taking calculus, but im not sure if I have already dealt with linear algebra before. Is it its own subject, or does Algebra and Algebra II cover the content?

Startup Engineering from Stanford on Coursera. Life changer for me.

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