I am enrolled in 2 MOOCs at the moment. I have completed several MOOCs in the past year and have found that the MOOC format with deadlines and tests works very well for me. It forces me to actually do the work at a certain time, since I have to meet deadlines or I won't pass. I have also enrolled in the "Signature Track" for these courses where I paid upfront for an "ID Verified" certificate if I pass. I believe this will help me complete it, as I have money on the table. I would love to have study partners for both courses. Below, I give some general information and a pitch for each.
Single Variable Calculus (Coursera) - Course Page
Requirements: Pre-calc, basic familiarity with Calculus (ability to differentiate and integrate a simple polynomial)
My Reasons: I never deeply understood Calculus in college, even though I could solve the problems in context. I feel that deep understanding of calculus will be useful for Probability Theory and more advanced programming.
My pitch for this course: The course materials are extremely high quality. (Tied with MIT's 6.00x for the best I've ever seen) It emphasizes deep understanding of relationships between different mathematical structures. It starts with the Taylor Series and uses it to develop the rest of calculus. It covers all of single variable calculus rigorously and concludes with building discrete calculus from the ground up.
Start Date: It has already started, but we're only in week 2. It would not be too hard to catch up and even if you don't catch up in time for the first quiz, it's only worth 4% of the total for the class.
Linear Algebra (edX) - Course Page - Outline
Requirements: Geometry, pre-calc, high school algebra. (I suspect that basic programming knowledge will be helpful)
My Reasons: Again, I never deeply understood Linear Algebra in college, even though I could solve the problems in context. Linear Algebra is important in many aspects of computing and programming. Linear algebra is on the MIRI course list (though I suspect that this course will turn out to be better than the Coursera course that is listed there. (Also, the Coursera course is not currently offered and does not have any upcoming sessions.) Additionally, the book on the MIRI course list says in the preface that it is intended as a second-pass at Linear Algebra and focuses more on abstract vector spaces and maps. I plan to work through the book after this course.
My pitch for this course: It appears to be a very complete course. It emphasizes computation throughout the course which appeals to me more than trying to memorize steps to solve problems by hand. There are programming assignments throughout the course to teach linear algebra in the context of computation instead of in a vacuum. I imagine it would be much harder to start applying LA to programming if you learned them completely separately.
Start Date: January 29th
I thought I had a pretty good understanding of Linear Algebra until I worked through the 1st chapter of "Structure and Interpretation of Quantum Mechanics". When I took Linear Algebra before, all of the material was very practical and so I missed the bigger theory behind the class. I'd like to really get that understanding.
I've actually become a lot more interested in the subject now that I see how much more there is to learn and all the connections with physics.
It would be mostly a second pass for the basic material, but I've never done the least squares analysis and I still struggle with the theory behind eigenvalues/vectors. There's a lot of material I would like to understand in the future, especially topology and abstract algebra, but I think this would be a useful start, and then I can continue to read through SIQM without getting overwhelmed.
I'd be thrilled to have you take the [edit: edX] course with me if you're interested. If you think it's too basic, then I'd recommend the book i linked above. I skimmed it and it looks very good. Also has great reviews. Let me know if you register for the class!
I just registered. I think it will help to go through the basics again just to make sure I'm not missing anything.
I'm also taking a database class offline here, but I should have plenty of time to work on linear algebra.
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.
I'm looking for study partners on a variety of subjects; introductory Japanese, the Less Wrong Sequences, programming, and more. Please message me on my Gmail at wolvenreign@gmail.com or at my Skype at wolvenreign.
Looking forward to hearing from any potential partners!
I'm hesitant to jump into something, but I'm also currently learning Japanese. I'm struggling through reading some comic books and I have some simple but infrequent conversations in Japanese over the internet. If you're past the basics and on to trying to parse large or complex sentences I'd be happy to study with you.
This is a great idea for a regular thread! Thanks for posting.
I'm taking Computing for Data Analysis on Coursera, which is more or less an R primer. There's only one more week left in my session, so there's not much time left to study together, but regardless I'm open to studying with other LWers taking the course. So far it's pretty good, so I can recommend the course if you're thinking of taking it.
I probably won't have much time for MOOCing in the near future since next week I'm starting a new job that I expect to be intellectually demanding and I'll want to do other kinds of things in my free time. But you never know.
Edit to add: I'm also on Lesson 5 of Differential Equations on Udacity, but since it's not timed I've put it on the back burner. I'm planning to finish it up once the R course is done.
If you're interested in Data science, Coursera just announced a specialization in data science by the same team teaching the course you're currently in. It looks very promising.
I'm looking for a study partner to study the book "Machine Learning in Action" by Peter Harrington (I have it in pdf). I want to read it and do the exercises in approximately 8 weeks.
That's currently sitting on my desk, staring at me suggestively.
I've got borderline too much stuff on the go right now, but depending on what you're looking for in a partner I might be interested. Just FYI, I don't believe this book contains any exercises (although we could work through the examples).
If you're willing to wait until March to start, I'm definitely interested!
I will read this book in order to (among other things) help me in a project I have to do for April, so March is to late for me. If you decide to start reading it now but don't finish it at the same time than me (or stop reading it at some point), I won't mind. And if you start it later (ex.: March), I'll probably have finish it, but if you have question at that point don't hesitate to ask me anyway.
It's the first time that I'm looking for an online study partner. I think it can be useful to motivate each other, talk about the subject, ask the other if we don't understand something or have a problem with our program, etc. But this is an experiment for me. So I'm not looking for anything particular in a partner.
Here's my current study pipeline. If you see anything that marries up with what you're doing, I welcome high-context online penpals.
Official / expensive-piece-of-paper studies
Statistical methods (linear models, multivariate analysis, Bayesian techniques; I'm wrapping up a part-time econ/maths degree at the moment.)
MOOCs
Vocational
Much to my surprise, I became a Perl developer a few weeks ago. I'd describe my perl as modest at best, so I'm working through O'Reilly's Programming Perl(4e). This book is slightly longer than The Lord of the Rings, and I'm going through it in 10-20 minute bursts at work. I know it's unlikely, but if anyone else is in a similar position, it'd be nice to have a spotter.
Misc.
I'm quite terrible at coming up with mathematical proofs. This seems to be a common problem with people who've done mostly applied/methods mathematics but not a lot of pure/analysis stuff. As such, I've picked up Pólya's How To Solve It and Solow's How to Read and Do Proofs, both of which I will be working through when the time presents itself. I think having extra people to ask "seriously, where the hell did that come from?" would be extremely valuable in this area.
Hi,
I have to pass the Mathematics Content test (Mega Math for High School).
I am looking for an online study partner to exchange notes etc.
I have to prepare and pass the test in one month. I have to do the test at the end of this month.
Hey Noshi,
Not sure this is really the right place to find what you're looking for (this is a 5 year old thread).
I am looking for study partner for EENG 150 and EENG 383/388 classes. I am taking these classes through Eastern Washington University. I am hoping that we can meet up through Skype to study for exams and quizzes, exchange knowledge. Send me a mail at 29.waiyan@gmail.com, please be quick before Fall 2018 ends. Please do not send Spam mails, Thank you !
I am looking for a study partner who wants to Machine learning concepts with me and perhaps even work on some mini projects together. It should be someone who is serious about Data Science and ML. At the moment, I'm going through Jason Brownlee's excellent ("advanced") primer on LSTMs as well as reading Kaggle threads on LSTM classifiers that ranked highly in the Kaggle competition. What I'm missing is fellow learners willing to hash through the material to discuss and clarify ideas. Want to join me? Feel free to contact me at: john.strong@etherpros.com (john dot strong at etherpros dot com)(website: www.etherpros.com).
I'm generally interested in Math, Statistics, Computer Science, and Science, particularly Physics and Chemistry. I already have a good training in Math, up to some advanced undergraduate Linear Algebra, Real Analysis, and Modern Algebra, etc. My Science training, though, is very weak and I only have a passing understanding of Newtonian Mechanics. And I can program with some basic facility in Python. I'm always enrolled in some kind of a MOOC (right now, Intro Comp Sci as a refresher and a CompSci-esque Linear Algebra course) or reading this or that text, and I'm open to any sort of project that could expand any of these skills. I particularly like learning a subject both from a foundational (axiomatic, definition-theorem-proof style) perspective as well as with a focus on understanding, interpreting, and getting the philosophy behind something.
If anyone's interested in teaming up on a topic, I'd be happy to have a study partner so please do send a message.
I'm trying to get back into studying Japanese (I did a lot of independent study and took 3 semesters of college classes, but proficiency this is not). I was hoping to try studying with a partner starting in February, but I've gotten out of the habit of signing in to Skype (automatically signing in / remaining signed in at all times has lately become more trouble than it's usually worth).
I'm also hoping to improve my skills with math (I kinda bailed at Calculus II), programming (I can make games, but an expert I am not), and music (composition/performance, though I'm not sure if there's a way a study partner could help much with these, unless someone can verbally correct my keyboard/guitar fingering). Doing these optimally may require clever solutions for accessibility reasons (mathematic notation online is often rendered as screen reader unfriendly images, for example).
I'd prefer a consistent schedule, but I don't have any idea what my availability will be like during March (I assume it will be less uncertain from April to August). For now, I know only that 7AM-12PM US Central time, and 3PM-6PM are unavailable in the short term (this will almost definitely change soon).
Great idea for a monthly thread!
My current studies:
I've never taken Precalculus, so I'm using ALEKS ($20/month) for that. I'm hoping to take the Coursera Calculus MOOCs when I'm finished. I'm open to alternatives though. If I can get a study partner for the Art of Problem Solving books (Intermediate Algebra, Precalculus, Calculus) that might be ideal.
I signed up for the Johns Hopkins Data Science MOOC series starting April 7th. I only signed up for the first in the series so far.
I also signed up for the Rice University Fundamentals of Computing series starting March 24th. Again, I only signed up for the first in the series so far.
However, the main reason I signed up for the MOOCs is because I need the time / social pressure of keeping up to schedule. A study partner might do the same thing, in which case I'd be interested in studying anything leading to a data science career.
I'm going through the PGM coursera class (It's one of the classes in the MIRI course-list). I'm definitely going to finish it because I'm doing it as an independent study at my University.
I'm taking the class with 2 of my friends from school who also read LW. Message me if you'd like to study with us.
I would be interested in finding a study partner for Mandarin. I am at an intermediate level currently.
I'm looking for a study partner to read Skiena's Algorithm Design Manual. I'm a math student who will soon be looking for a job in software development, so I'd like to read and grok the first 10 chapters over the next 2-3 months.
For reasons mentioned in So8res article as well as for other reasons: studying with a partner can be very good. In November, Adele_L had posted an article for people wanting to find a study partner. It got 17 comments, but only 1 since November 16th. So I thought we (I) should make a monthly thread on this instead of constantly going back to an old article which people might (seem to) forget about. If people seem to agree with that, I will make a post about it every month.
So if you're looking for a study partner for an online course or reading a manual (whether it's in the MIRI course list or not) tell others in the comment section.