I’m active on Coursera—currently taking Game Theory II. Other courses that just started but look interesting include Cryptography, Computational Molecular Evolution, and Information Theory. I’m up to try one of those or any other quantitative course that looks interesting with a study partner.
Also, I have a decent background in data science/machine learning through Coursera courses but not much practical experience. If anyone wants to partner for either a competition (something like Kaggle) or to analyze a real data set, I’d be happy to work on that.
I quit the Coursera information theory one because it was presented so drably and gave very little high level insight into what was going on. It was essentially just the guy reading from the textbook. It’s all the things wrong with traditional teaching with none of the benefits of MOOCs (aside from the forums).
I’m currently working my way through these lectures. The instructor is engaging, and actually explains what it is we’re doing and why we ought to care. I’d be on board with working through them together!
I had the same issue with the Coursera class, but thought it might be tolerable with a partner—this looks much better, though. I’ll message you to discuss details.
I’m also working through Game Theory II on Coursera right now, as well as Social and Economic Network Analysis (presented by Matt Jackson, the Stanford contributor to Game Theory II).
I’m planning on starting Discrete Optimisation in March, but it looks like quite a high workload, and I have other study commitments around then, including exams, so may bail out of it at a moment’s notice.
I took Game Theory I on Coursera, but one stupid late-night decision (involving football and strippers) made me forget to take the final on time. I was thinking about doing Game Theory II, but I don’t know if I’ll have time to finish with my current workload (see my top level comment above). However, I’m finding that watching a weeks worth of Game Theory videos actually helps me switch contexts and recharge vs. doing hard math, so I may try to work my way through it (I’ve completed week 1 already and it didn’t really take very long).
If you and Markas are interested, we can have a little 3-way mailing group or something
That sounds great. I haven’t finished the first week’s material yet, but I’m planning to tackle it tomorrow, and I assume the difficulty/commitment is comparable to Game Theory 1. I’ll message you both with contact info.
I’m still on the fence regarding Network Analysis (though I haven’t started the work yet, so that may not longer be an option) and Discrete Optimization—I’d be curious to hear your thoughts on both. I’m currently finishing up Bioinformatics Algorithms I, which also had an extremely high workload, so I’m inclined to lean towards fewer total classes unless I’ve underestimated how relevant or engaging those particular courses are.
I didn’t actually do Game Theory I on Coursera, but I’ve had a number of pretty thorough introductions to game theory, and I’ve touched on social choice theory as part of my degree. My intention with Game Theory II was to flesh that aspect out a bit more formally.
Likewise with the Network Analysis and Discrete Optimisation, I’ve had some pretty thorough introductions to graph theory, combinatorics, discrete mathematics, etc., but I’m keen to get a flavour for different applications. Also I like the practical aspect of Coursera courses. My discrete mathematics course was taught as a maths course rather than a computing course, so it was removed from a practical context. It’ll be nice to actually code these things up rather than just talk about them in the abstract or work through them by hand.
I set up a google group here for the Game Theory course. I set up a first post as a bit of an introduction and a place for anyone who joins to say why they’re taking the course.
I hadn’t heard of the network analysis course, but it looks interesting. I like Matt Jackson as a presenter so this looks like a good course. I don’t have time for it right now.
I’ve had my eye on the discreet optimization course for a long time now. I would really like to be able to take it this offering if my schedule permits, though I expect it to have a very high work load. I imagine there would be quite a bit of interest on this one in the LW community so it would be interesting to gauge interest as we get closer to the start date.
I’m active on Coursera—currently taking Game Theory II. Other courses that just started but look interesting include Cryptography, Computational Molecular Evolution, and Information Theory. I’m up to try one of those or any other quantitative course that looks interesting with a study partner.
Also, I have a decent background in data science/machine learning through Coursera courses but not much practical experience. If anyone wants to partner for either a competition (something like Kaggle) or to analyze a real data set, I’d be happy to work on that.
I quit the Coursera information theory one because it was presented so drably and gave very little high level insight into what was going on. It was essentially just the guy reading from the textbook. It’s all the things wrong with traditional teaching with none of the benefits of MOOCs (aside from the forums).
I’m currently working my way through these lectures. The instructor is engaging, and actually explains what it is we’re doing and why we ought to care. I’d be on board with working through them together!
I had the same issue with the Coursera class, but thought it might be tolerable with a partner—this looks much better, though. I’ll message you to discuss details.
I’m also working through Game Theory II on Coursera right now, as well as Social and Economic Network Analysis (presented by Matt Jackson, the Stanford contributor to Game Theory II).
I’m planning on starting Discrete Optimisation in March, but it looks like quite a high workload, and I have other study commitments around then, including exams, so may bail out of it at a moment’s notice.
Uh...wanna hang out? :-)
I took Game Theory I on Coursera, but one stupid late-night decision (involving football and strippers) made me forget to take the final on time. I was thinking about doing Game Theory II, but I don’t know if I’ll have time to finish with my current workload (see my top level comment above). However, I’m finding that watching a weeks worth of Game Theory videos actually helps me switch contexts and recharge vs. doing hard math, so I may try to work my way through it (I’ve completed week 1 already and it didn’t really take very long).
If you and Markas are interested, we can have a little 3-way mailing group or something
That sounds great. I haven’t finished the first week’s material yet, but I’m planning to tackle it tomorrow, and I assume the difficulty/commitment is comparable to Game Theory 1. I’ll message you both with contact info.
I’m still on the fence regarding Network Analysis (though I haven’t started the work yet, so that may not longer be an option) and Discrete Optimization—I’d be curious to hear your thoughts on both. I’m currently finishing up Bioinformatics Algorithms I, which also had an extremely high workload, so I’m inclined to lean towards fewer total classes unless I’ve underestimated how relevant or engaging those particular courses are.
I didn’t actually do Game Theory I on Coursera, but I’ve had a number of pretty thorough introductions to game theory, and I’ve touched on social choice theory as part of my degree. My intention with Game Theory II was to flesh that aspect out a bit more formally.
Likewise with the Network Analysis and Discrete Optimisation, I’ve had some pretty thorough introductions to graph theory, combinatorics, discrete mathematics, etc., but I’m keen to get a flavour for different applications. Also I like the practical aspect of Coursera courses. My discrete mathematics course was taught as a maths course rather than a computing course, so it was removed from a practical context. It’ll be nice to actually code these things up rather than just talk about them in the abstract or work through them by hand.
I set up a google group here for the Game Theory course. I set up a first post as a bit of an introduction and a place for anyone who joins to say why they’re taking the course.
I hadn’t heard of the network analysis course, but it looks interesting. I like Matt Jackson as a presenter so this looks like a good course. I don’t have time for it right now.
I’ve had my eye on the discreet optimization course for a long time now. I would really like to be able to take it this offering if my schedule permits, though I expect it to have a very high work load. I imagine there would be quite a bit of interest on this one in the LW community so it would be interesting to gauge interest as we get closer to the start date.