- 91 reviews
- 66 completed
Fairly short practical oriented course on statistics which teaches you some R. I think the UT-Austin course on edX, Foundations of Data Analysis is probably a better way to learn statistics and R than this course. However, that course has numerous errors due to carelessness, and you don't get that with a course from Harvard. So you'll have to decide. Also, if you have less available time, this one takes half the time as the Texas one, (with the expected shortcuts in the amount you will learn and/or retain). This and the following 2 courses were part of a longer course PH525 previously offered. While it is nice that you can finish this course anytime within a 4 month window, I kind of would like to get my certificate as soon as I tell edX I'm finished (or I have answered all the possible assignments). As I finished a little late after the first deadline, now I need to wait 3 months.
This course is designed for people who know nothing about stats and are unlikely to ever want to thoroughly understand them. You memorize things (doing simple, mostly guided, graded exercises in R and more interesting contexts of the problems makes this easier). But hopefully you don't apply this memorized info too frequently (and become a wise fool). If you want to get deeper into stats, perhaps the MOOC from Duke is better. On the other hand, this MOOC is significantly better than the Johns Hopkins stats course, though that is admittedly a low bar. There are various nits that keep it from being an exemplary course. In general it is due to sloppiness. The instructor sometimes says one thing, then says something else about the same issue (e.g. what the t-statistic says about the null hypothesis). At times the instructions are a bit too vague, while the grader has zero tolerance for imprecision, some parts of the course have some errors (some are minor, some less so) and so far I have not detected any effort on the professor to correct these. After a while the poorly worded questions combined with overly aggressive grading strictness led me to first search through the poorly organized discussion board to find out if the question is poorly worded (because you only have one chance to get a question right). This has happened so many times that the professor has had discussions about this in his "optional" weekly Google hangouts (this appears to be mandatory to do well in figuring out the problems) and various problems have become ungraded, or the number of attempts is removed, a few questions near the end of the course specifically point out steps that are assumed in most of the course (like use the rounded answer from a previous question to calculate the current one). This course doesn't look obviously bad like the Johns Hopkins one. Its problems are more subtle and require you to become engaged before their distracting "Chinese Water Torture" nature becomes more obvious. The more I work in this course, the more this overall sloppiness becomes more annoying and distracting from my actually learning things. I would prefer something that imparts deeper understanding. Though if all you're after is an introduction, it is OK.
The course is a mixture of lectures from 10 different instructors of varying quality depending on the lecture/topic. For example, I recommend you skip the big data architecture part of this. Normally I give high provider score for Coursera MOOCs, but this is not like any Coursera MOOC I've ever taken. There are no graded assessments of any kind. This is more like a YouTube channel than a MOOC. There are maybe a dozen to 2 dozen messages on the discussions forums since they were opened a half year ago (i.e. they are dead). I'm just starting this course, so I will update this review as I learn more. However, my gut tells me to wait until they revise this course (supposedly in the Spring) to be more like a normal MOOC.
This class is MUCH harder than their Game Theory I class because it is VERY abstract. The videos gave virtually no examples and used lots of terminology with the tacit assumption that you either already knew the terms or virtually immediately understood them when they first sort-of explained them. Unlike in their original version of the Game Theory I class I took, the professors were absent from this class. It was run on autopilot. This class is a disaster. One student persevered, chasing down other texts to figure out how to do well in the class. He got 100% on every test but one (getting a 99%) but it took him 50 hours a week to do this. The professors need to redo this course from scratch. They are excellent in their fields, so I have no doubt they can. Until you hear if they have rewritten the course, DO NOT take it. Wait until they fix it or try to find some other source for this learning. Update: The above review was of the 2nd iteration of this course, run in early 2014. I briefly sampled the 3rd iteration in early 2015 and it seemed better (but I didn't have time to look into it further due to other time commitments).
First iteration: Very thorough course with extensive work done to make the programming to teach this viable. I only had time to skim this first iteration of the course (just enough to meet the low requirements for a certificate ) Second iteration: I'm taking this again to learn this material very well as other courses I've taken don't cover this material nearly as deeply. This professor really wants you to understand fundamental concepts rather than just memorizing techniques that could be misapplied if one doesn't understand the fundamentals. The professor goes out of his way to create explanations for the quizzes/homework ... including recording short videos to explain it, posting downloadable explanations, etc. This iteration of the course also includes a license of Matlab for the duration of the course.
As a creator of some of the techniques explained in this course, the instructor clearly has deep knowledge about the material he presents. However, he is not a teaching specialist, so learning the material is somewhat of a challenge (somewhat more so for those unfamiliar with east Asian accented English.) For those having problems learning solely by the videos provided, I recommend reading the free chapters from his book, which the course is based on. It is good that the instructor has setup forum subforums, such that there is a subforum for each video in the class. I wish there was programming in the class as I find that often helps me to better learn the material. The material is somewhat abstract so you have to concentrate more in this MOOC.
The instructor seems fairly well-informed. However, he is not an engaging presenter (not boring, but not engaging either). The instructor's speaking style is somewhat tedious because he so frequently makes long pauses in the middle of his sentences. You can speed him up to reduce the length of the pauses and hence the videos, but then other parts of his talking will be quite fast. Assessment in this course is very easy and academically a joke. It is not too conducive to encouraging deep, lasting learning. The quizzes, which count for 70% of the grade, are identical copies of the end of video quizzes. The final is a repetition of almost every question in the quizzes in virtually their original sequence (and hence the video quizzes too). You can take all the quizzes AND the final, up to 100 times, the questions don't change with each submission, and they are all multiple choice. So if you don't care about learning and just want to get a certain grade, "multiple guess" is easy. That being said, if you are a parent of bilingual or are thinking of doing so, or you are one yourself, you will find the course interesting (and since there are no other college MOOCs on this subject, this is your only MOOC choice).
I really enjoyed this class and the professor's style. Doing his lectures outdoors was really inspiring too. Because I had other time constraints, if the professor ever offers this again, I will take this class again to fully appreciate it. In the mean time, I fortunately got a copy of the videos (thank you RT).
The google hangouts were more useful than most I see in MOOCs. The subject matter is well-presented. The sample games were sometimes interesting though I wasn't sure there were enough people participating in them.
How many ways can you say this class is bad? Well, if you had access to their forum, you could just read (or read the lack of) content to figure that out. But Venture Labs would prefer you not do that, so they close it off to anyone who hadn't signed up by a certain date.
I wish I had more time for this class. The professor was engaging, the EDX platform is superb, and the homework assignments were very fun. I am taking this soon (after a 2 year wait for iteration 2) so I can really take advantage of the class. Stay tuned for updates.
I almost completed this excellent class, when another high priority took all my available time. I finished a slightly shorter version of it later and am soon starting the next course in this sequence.
The instructor (NOT a professor) spoke so slow and wrote so many emails out of his own insecurity, that I dropped this class sensing that this instructor was in over his head.
AWFUL Run away from this class. There is no enthusiasm for it from the students (i.e. virtually no participation). The professor just includes a bunch of canned videos from various people done for other reasons besides this class, plus some old videos he did in amateur fashion. There was virtually zero participation by the professor on the discussion forums (and he has no one helping him). The previous version of this class sucked, but I felt I could do something about that, and recruited the best talent available for my team (many said they only took this course after not liking the prior course only because I was leading the team). I was overly optimistic but we did the best we could. I even created a separate invitation only forum to stimulate discussion because the actual class forum only had 1 or 2 postings PER DAY from the ENTIRE class. Frankly, Stanford should ban this professor from teaching this course. The professor openly admitted he had no time for the class having to spend his time on research and advising graduate students. This class is an embarrassment on one of the best half-dozen universities in the world. I only took the class in order to give some people a framework to complete a project we were doing. We were the "top team" in the class despite the class, and even then our work wasn't that great. The class was a downer for my team that I had to spend a lot of time overcoming.
This course showed me the adage of you get out what you put in. I signed up for the course as a lark. But after the first week, I got sucked into at least an 80/hr week investment working with a large team of highly creative people (for those of you who took the class in 2013, I was the team lead of Global Roots -.a sampling of the work we did for the class is at http://globalrootscreative/stanford_gallery). For me, this class was a framework to do something creative with people that wasn't possible for me locally. I learned from the other people on my team and from a few folks on other teams. I didn't learn much directly from the professor. I think of her as more as someone who built an environment to encourage creativity, not to directly teach it. (In fact there is an excellent John Cleese video where he discusses the notion that teaching creativity is nearly impossible). Yes, the videos from the prof were only a few minutes. If you were looking for a bunch of tangible materials to teach you creativity, they weren't there. But for those who put the time in to be creative, and to be inspired by others working on the same goals, it was a great way to do this. And I say that despite the fact that Venture Labs (now NovoEd) has the ABSOLUTE WORST MOOC platform and generally has bad classes "taught" by people who will never be the "rock stars" of the MOOC generation (and lately they are trying to charge for this junk). Large segments of the class had LOTS of technical problems with this MOOC platform. Fortunately the professor did her best to be actively involved (reading HUGE volumes of mail and postings) to help smooth things out. Those problems were opportunities to be creative and find solutions rather than complain...though we did complain too;-) So I say, DESPITE all those problems, this was one of my all-time favorite classes (MOOC or traditional college).
This is admittedly subjective, but I didn't like the professors voice. And if you're going to listen to hours on end of someone, that can be a problem. But it was my first MOOC and I wanted something that said Stanford on it, so I persevered. Since I've been working in the database field and have also written and taught it, I didn't expect to learn much. I was a bit disappointed when the professor made several statements that go counter to what the thought leaders in databases would say.
Really good short class that all entrepreneurs should take. He really hammers home the importance of talking to potential customers first before wasting a lot of time building the wrong product/business. He also has a pleasant delivery.
It is a so-so class. The best thing is it made it clear why further study and application of social network analysis can be very useful. On the down side, the professor seemed a bit too casual/loose/amateurish/unprepared. She was not one who exudes confidence and therefore makes the audience confident that they are learning the right things. After going through the entire course, I feel she is quite knowledgeable, but it isnt't something that comes off on a first impression. She also had some weird/wrong vocabulary or grammar that was not correct English, which made me wonder if English was her native language (which it is). As I was simultaneously taking the Excellent AI class from Berkeley and Excellent Intro to Programming class from MIT, her weaknesses were more apparent due to the contrast with these fine courses.
Amateur hour Videos are mostly just a video of a live class (including mostly inaudible and non-useful questions from the students in the class). The other videos were someone standing next to a wall with a projected image of slides or text in too small a font. I'm not even sure how someone in that room could view that unless they stood right next to the wall. No syllabus, no grading/certificate info. Boring, redundant videos with little content and content that was often outdated, practices that are no longer considered best practices. I know they focus on life sciences so some things are different than with IT startups, but the instructors need to have a serious chat with someone like Steve Blank to figure out how adapt the new best practices in IT to their industry. Watching this class made me feel like it was 30 years ago. Ugh. Though I would like to learn info on financing startups I had ZERO confidence I would not be mislead down the wrong path by these instructors. So I dropped it.
Eons ago I got a B.A: in Math from an elite university. I barely used it since until now, so I wanted a refresher. Not expecting much from a mid-level university, I was pleasantly shocked by the extremely entertaining teaching of Professor Fowler and his group. If you were ever reluctant to take a calculus course, please take professor Fowler's class. Or if you want to learn how to teach or improve your teaching even if you have no interest in calculus, take his class. You will find the experience rewarding.
Another great course from Jim Fowler (see my review of his Calculus One class. http://coursetalk.org/coursera/calculus-one). The course is easy if you only want to pass it because you can repeat things so often and there are so many hints. If you want to actually learn (and remember it) there is a large amount of material to look at.
I felt like I was taking a class at a community college, or maybe in high school. The teacher did not exude expertise in her field... mainly I got the idea that she's been in the field since its infancy, so kudos for learning something in all those years. But I think someone else will do a better job teaching this class.
I took the 6.00 class earlier this year but had to drop it due to my time constraints. Now they appear to have chopped the class into two parts (perhaps with some additional material). The class is as well taught as last time. I definitely recommend it. The homework problems are fun. Sometimes creating little games.
This class is HARD. But I like the challenge. Usually, courses from elite universities are watered down when they become a MOOC. Perhaps there is a more lenient grading curve for MOOC participants, but as near as I can tell, this is the same material the CalTech students get. (Reference point: at CalTech, getting 770 out of 800 on the math part of the SAT means 75% of your classmates scored higher than that). I am currently taking the Stanford Machine Learning class (which others have mentioned is watered down from what Stanford students get) and I have taken the Berkely AI class and this CalTech class is definitely harder than those two.
You can spend less time and get a decent grade in this class, but if you want to write something creative under the (IMO) too restrictive constraints of the assignments, you'll need to spend more time. 12+ is not out of the question unless you are a digital Mozart. I've never mixed making music and programming before, so this is fun. Even if you don't aspire to make something original and musical, you can have a lot of fun making weird sounds with your programs.
I had to drop this course over half-way into it due to unplanned time constraints. I was definitely interested in the topic and it was my first class from a non-US university or non-elite university so I wondered what that would be like. I think the later (non-elite) was why I too often found myself sharply disagreeing with the professor's views. I've been in business intelligence for well over a decade and in databases for two decades and try to learn from the best. This professor was definitely not in that category. Still, it was a new area for me, so I persevered until my time constraints were too much. I would take it again if it was offered (to complete the material) and I'd try to ignore the wrong things the professor said. For those with far less experience I am afraid you may be taught wrong things, so be skeptical when something doesn't sound right and watch the forums for discussions on those topics.
If you are thinking of starting a business, this is a good subject to learn. To get the basics (and pass the class) is pretty easy. The instructors are earnest in a 1950's kind of style (including their dress).
The professor talks too fast and makes a lot of claims about statistical techniques but gives no explanation what those techniques are.Still, the topic is of great interest to me, so I finished the course. Yes, the professor speaks too fast and references lots of items that are unexplained, but the class is worth it. I also like his sense of humor. He spent a lot of time monitoring the forums which was nice (and unusual in MOOCs). For those who have little background, you could consider this an Intro course to just be exposed to many techniques. I plan to dig further into the resources, now that the class is over. Also, there isn't much about Big Data in this course. They should drop that from the title. However, data mining, analytics, machine learning techniques are all covered. The professor is clearly at the forefront of applying this to educational data, so if you already know the main techniques, but don't know what works best in education data, this is an excellent class to take.
The professor's videos are engaging. This was an excellent class though to really get the most out of it requires you to do some serious thinking about yourself and your life and do things outside of class that may take you out of your comfort/passive zone. And who knows... that may just change your life!
This class does not have a lot of material, so it is easy to pass the course. Nevertheless, the material that is given is very valuable and the videos showing the concepts in the real world are excellent. I also recommend parents take it. And although the material is geared towards kids under 5, many concepts can be used or adapted for older kids. Adults too;-)
This was a refresher class for me to make sure I didn't miss anything important prior to taking refresher calculus courses. So it was very easy for me, so depending on your background and skills you should expect to spend more time per week on this than I did. For most students I would rate the class as medium, though with one caveat for MOOCs. Most MOOCs give you a VERY long time to complete exams. In this class, 80% of the grade is the final exam and the time allotted for this is closer to what I would expect from an exam taking on campus.
I felt like too little non-obvious information was presented. I'm also not a big fan of courses that only expect you to spend 12 hours on them, but for a counterpoint, the 10 hour course from Coursera/University of Virginia - Effective Classroom Interactions: Supporting Young Children's Development imparted far more information of value. I think this course tries to cover everything about early childhood superficially rather than being much more focused like the University of Virginia MOOC. VERY easy class (30 -60 minutes per week). The tests are absurdly easy. Common sense, particularly if you've ever had a child or spent significant time around a child will enable you to answer most questions without watching any videos. You will learn nothing earth-shaking and I fear that really advanced educators (the instructors are not professors) in the field of early education may say things at times radically different from the mostly conventional wisdom imparted in this course. Also, this class (and I presume most class) comes from almost entirely an Australian perspective, so if that varies greatly with your background, consider the difference between science and culture when evaluating the usefulness of something said in the course. I suppose this course still has some value, given the short time commitment.
This class is quite easy and short (just 4 weeks). Actually the test taking process makes it too easy to get 100% for a course from Coursera offered by a decently ranked university. The technology presented by the teacher is old hat for the typical person who keeps up with popular internet sites. I would prefer if the teacher was more knowledgeable. It is not taught by a professor or even someone with a PhD and her lack of detailed info shows. That being said, there are a number of resources pointed out by the instructor that MAY prove to be valuable. If evaluating those proves to be fruitful and if you spend time for the peer reviewed assignment to do quality work, the class may be worth it. I was very disappointed to see that the peer review assignment had no space to provide comments. The instructor is in charge of all MOOC offerings from her university and claims to have overseen 14 MOOCs so far. The quality level in her MOOC (and another one I took and dropped) suggests that her management and teaching skills need a lot of work for someone at a good university. If it weren't for my good experience with the university's pre- calculus class, I would be tempted to stay away from all Univ of California- Irvine MOOC offerings. As it is, I will be wary when I take another one from them. There is an advanced class from the same university starting in January 2014. Hopefully that one will be more worthwhile.
As this is a Venture Lab (NovoEd) course, the key component is team work. Unfortunately they dropped the true teams to have psuedo teams (basically a study group) and the normal drop off rate in MOOCs (even Team-oriented MOOCs) predominated. The only other person in my study group who somewhat participated with others in the group, dropped from the study group because no one else but me was reciprocating that participation. So effectively, that ended my group just 1 week into the course. I hung around another week or so because at least the forum was heavily used. But it was too heavily used and too poorly organized for that much traffic. A team MOOC is a great idea. But it is rare to find it well executed. This MOOC was not one of those rare exceptions for me. The professor also dominated in the forums instead of letting other voices blossom. Mostly it was fun working on the assignments and occasionally seeing good examples of the work from other students. The MOOC platform often buckled under the light loads of this class. Website outages were all too common. This class was potentially an excellent idea. The outcome (at least the first half that I stayed in it) was not so great.
With all the promotion of the U of Maryland and the group there that the instructor leads, as well as his book, and the fact this is the FOURTH iteration of this MOOC (with a 5th starting in less than a month) and the cheaply produced material never being updated, it is clear this class is a business that should be relegated to one of the lesser educational platforms than Coursera. This is not a good course for scalable, rapid growth, innovative startups. They should drop the word innovative from this class. It is standard boring business school stuff, perhaps useful for middle managers in huge companies, or for someone starting a mom and pop business who knows nothing about business and has no other better sources for information. The boredom of this class is not surprising since the "professor" has only spent 3 1/3 years working in startups, and NOT as a CEO or co-founder, but rather some manager. He has spent nearly his entire adult life in college. So his comments are stuff you can read out of some academic business school book. It could often take 3 hours just to watch the videos, but the speech is so slow, speed it up and you can do the class in 2 hours a week. This is the first course (of the over 30 MOOCs I've taken) where turning the speed up to full (double speed) still had me waiting too long for the professor to say anything interesting and at no time could I not understand him at double speed. He just has too little to say and is padding out his lectures and slides will filler. I am disappointed by this course. Having completed Steve Blank's excellent if short Startup MOOC on Udacity and the potentially good, but weakly executed entrepreneurship course on NovoEd, I was hoping for a substantial and well- prepared course. This is the worst business course MOOC I've taken. It often takes a large enterprise approach leading people about factors that no successful entrepreneur would bother with until some years after surviving the initial period of finding the right business model. The lectures are slides with a tiny inscreen videos of the professor in his class teaching students at college with a lot of time spent asking questions of these students. This is almost as low budget production values as it gets in MOOCs and is at odds with a course on innovation. NOTHING is innovative about this MOOC. With all due respect to the students (I remember what I was like at that age), I really don't want to waste time listening to their naive answers. I come here to learn what an expert has to say. Also, this is beginning MOOC style... just film the professor lecturing in class. It is pedagogically antiquated and basically lazy. The professor should learn something about teaching online.
The speaker speaks too slow given that this platform has no native ability to speed up the video (unlike Coursera or EDX). After clicking on your video's YouTube link, I was able to download the YouTube video so I could play it on a video player with speed up buttons. Most of the answers on the pop quizzes and also too many on the assessments were answers that only an idiot would choose, so it was rarely hard to answer a question. Compared to the only other Open2Study class I have taken (Early Childhood Education) Mr Boyd was clearly more educated about his topic. It would be more interesting to see what kind of MOOC he could present if he were presenting on a platform with more expansive goals. Like many (all?) courses on the Open2Study platform, this time requirements in this course are minimal (i.e. an hour a week) and the tests (simple multiple choice) are largely easy/obvious. This one though is a bit more thoroughly produced than the platform's Early Childhood Education MOOC. For example, after each question, the teacher comes on to explain the right or wrong answer. The material is relatively informative/interesting and certainly not just common sense facts. However, do not mistake this MOOC for the quality and completeness levels on Edx or Coursera. It is far below those levels. This was my second and I think last Open2Study MOOC. They are aiming too low for me on the education/goals/intelligence spectrum.
This is a controversial class because of some of the choices by the professor. Personally I was relatively unaffected by the sales pitch for the social psychology network, but I can understand others' beef with this. Since I'm liberal, the liberal viewpoints of this professor, like 90% of social psychology people is generally not a problem for me, but I did get annoyed at one weekly assessment that was strongly promoting veganism and trying to persuade me to change. I saw no value in this assessment as it didn't relate to the week's materials. On the plus side, the videos are very interesting and it is clear that the professor is giving you an introductory social psychology class that incorporates views (and videos and papers) from the leading social psychology researchers of the past and today. So in that sense it seems quite comprehensive. However, so far the assessments really suck. So I'd give it nearly a 5 for course materials and nearly a 1 for assessments. I also think if you are in the minority of people checking out social psychology and who have a conservative political viewpoint, you are likely going to dislike a lot of this course.
They have many of the top chefs in the world in this class with some of the top food scientists. What a great way to learn science. I hated chemistry in college, but now I have a reason to learn about it. Great fun! My hard rating is only because I never really learned chemistry before, and now want to understand fully what they are doing, which makes the chemistry part of the course hard. If you are good at chemistry, I would rank this as easy.
BLECH! If it isn't immediately obvious to you that this class is devoid of original thought after spending 10-25 minutes viewing the first week videos, this review can not help you. It has slick (though not hard to create) production values to make you think you might be getting a quality learning experience. Instead, you learn about what some group trying to standardize what is not academically researched (at least by them)... how learning online approaches can be effective or not. Instead we get banal slides (with "cool" sound effects or background music) that might as well have been: In this course you are going to read * Words * Sentences * Paragraphs * And Sections! And then you get an in-video quiz asking you bullet point words you just saw. In one slide I learned we can read some material about blended and online learning usage outside the US. In a report from 2006!!! How about tell us what happened in the stone age? And here is some groundbreaking information I'm sure every teacher will want to learn from this MOOC (from one of their slides with a happy, vacuous face on it): A teacher INTRODUCES Content ASSESSES Regularly ADJUSTS Instruction FACILITATES Communication and Collaboration PROVIDES Feedback The only thing worse would have been if they had made some absurd acronym out of that slide and tested us on what words made up that acronym. THIS IS AWFUL: No wonder I never heard of Kennesaw State. The UC Irvine education MOOCs have been bad enough. I'm not wasting another minute in this MOOC. I suggest you do likewise.
I began my MOOCaholicism with his Game Theory class a year ago. The professor is clearly competent (further proof is found on his impressive curriculum vitae). I am beginning to wish I had not wasted my time in the Social Network Analysis class and just taken this class instead. While the professor's style is modest despite his impressive credentials, this also has the effect that he is not emotional enough, exciting enough to help students who aren't totally into the subject already. Minor item: Some of the explanations" in the in- video quizzes are not really explanations. They are just regurgitations of the question. When you get something wrong, the professor should know at least some common reasons why you might choose a particular wrong answer and pointing that out and why it is wrong is more educational rather than a simple. "You are wrong" type explanation. In many Coursera classes, there is not even a button "Explanation" given in the in-video quizzes. It is preferable not to have this button, than to give useless explanations.
UC SD's Earth Sciences program is a fairly highly rated, but my initial impression is that this course is designed as a normal college course and isn't following the innovations that MOOCs have created. Making readings required before watching a video is kind of old-school too. There are NO CERTIFICATES offered for this course (unless you want to enroll in a full university course with the usual large fees). The main professor is very esteemed in his field, but he has no clue how to operate a computer. He CONSTANTLY flips to the wrong slide, back and forth and this gets quite annoying after you've seen him do this for the 100th time. Since a large portion of the syllabus is not of importance to me (I'm just interested in forecasting) and there is no certificate, I have no plans to take any tests. I also won't do any activities I don't find HIGHLY useful. I guess that counts as dropped. Given the alternative sources for this info (including one from MIT), I don't think I will be completing this course.
The course designer leaves major bugs for weeks that would have taken 5 seconds to fix. This thing is definitely not ready for prime time, unless you are a glutton for punishment or enjoy bug detection work. Stay away. Brain dead easy (if you don't count all the bugs). It may not be a good way to learn because it takes such tiny steps each way. I'm not sure. There are some seriously bad practices being taught in this class that defeat the reason why CSS was created and will result in giant messes once you use this advice on real world websites. If you aren't already a skilled software engineer/architect, google something like "Best practices CSS" and you'll learn what is important and what parts of this course to ignore/avoid/reject. It also has bugs. One common one is because of a dumb architectural error in their system - they apparently don't read your actual code, but instead run it and then attempt to query your system to figure out it ran right. This makes their system VERY browser/browser-setup dependent. When you have annoying bugs, and you don't know its a bug but think its because you didn't do something right, you can waste significant time tracking down their bugs. Check the forums, because it is likely a bug that others are complaining about. So when you get an error message saying you did something wrong, if it isn't obvious, it could very well be that they had a bug, not you. Minor nit for Codacademy (unless this is only a problem in this course): I like to be able to scroll left and right through the "pages" of this course, much like a book, with a simple arrow icon. Instead I have to go to the top left, click on a small button that displays a popup menu, and then click once more on the previous or next item. This is more tedious than a simpler more intuitive interface. From time to time, the display of what you are doing is wrong, out- of-date, empty. Another sign of bugs or the course builder choosing an architectural design that relied on things more complex than they were able to deal with.
Great introduction to what education can be like Due to a technical hiccup, I couldn't hand in a major assignment and due to overload from other courses and the time requirements to do the projects for this class well, I decided to drop this well over half-way into the class. But it is worthwhile class. If the only thing you do is watch the videos of real schools that are doing things right by innovating with blended learning techniques, this class is worth it. If you can motivate yourself to plan and then try out some of techniques (this is the final project), then you will have achieved something enduring and worthwhile. The other parts of the videos where the two professors talk are also good - they have a nice camaraderie between them. Warning: if you're school systems are archaic/conservative/highly resistant to change, this class may depress you. Or motivate you to change where you teach.
Me, my kids, several other relatives, have all been told we're being "spacey" or absentminded (and also creative). So I had many reasons for learning more about what some people may label this as ADHD. This course is pretty straightforward. The grade is entirely based on multiple choice questions. The questions aren't too difficult and you get 3 tries on a quiz. However, there are no dropped quizzes or late days allowed and you have to get at least 90% to get a certificate. Because of this and that I was overworked at the time with other matters, I decided to unofficially drop the course, but since it was unofficial I still have access to the class and I am currently enjoying reviewing all the materials. Stay tuned as I update this review with the results of that rereview. Another reason I took this course is that the Univ of Pennsylvania has one the best medical schools and psychology departments in the world. So I don't worry that I'm learning from someone not uninformed (important for a potentially controversial topic like this). Unlike nearly every other MOOC, the professor creates a single video per week. He talks deliberately (i.e. not quickly) so you probably want to use one of the speedup settings. The professor's delivery style is fine, but for those of us who shift attention more rapidly than the average person, it would be better if he was more exciting or broke up his lectures into smaller chunks. We don't just pay attention just because the course title orders us to "Pay Attention!" ;-) I didn't have time to finish the course during its regular schedule, but I continue to view videos and read materials from the course. I hope they offer it again so I can interact live with others in the class.
I really like the enthusiasm the presenters in this class have. There are a wide variety of people contributing to the videos. They take a lot of material from everywhere (not just academics) to illustrate their points. The video quality, just from a purely entertainment perspective is much better than typical MOOCs. It is well produced. The iversity platform is also technically and visually more interesting than nearly all platforms. Though it is new, from my initial intro, it deserves to be in the quality league of Coursera and Edx. And of course the material is of interest to me too. I like the story writing assignments and also the different perspectives from the variety of speakers. I was too swamped to finish the class during its schedule and according to the professors they have no plans to offer it again. I hope they change their mind. In the meantime I'll try to navigate the archive for videos and whatever else I can do there after the course is over.
The main instructor is a GOD of design. Udacity has rebuilt their messaging system to have a nicely functioning forum which this class is using.
This is not nearly as theoretical as the Cal Tech course, and the problems aren't as fun as the Berkley AI course, but it gives you a larger survey of techniques to apply to machine learning problems. Some of this material is quite complex. The programming exercises are simplified due to this, but some can still be quite challenging.
I started this class at the very end of it's first offering (because I didn't know about it before). The videos are very informative and the professor has a nice style. Because it was the end of the class, I couldn't participate in all the discussions and more importantly all the computer modeling the class has. One major beef--- the professor does not indicate how much different assignments count so figuring out how you are doing in the overall course grade is a mystery unless you get the same scores for every possible assignment. The professor didn't seem to care about this, but now that the course is on the EDX platform where this is mandatory, this problem is solved.
This class is suspect. It comes from one of the top computer science departments in the world, so it should be better than this. The installation problems of Android SDK are significant and this class only covers some of them. Many students dropped out during the first week of this class soley because of this - if you can't get Android running on your system, the rest of the class is pointless. The first 5 weeks of the class are supposed to be for non-programmers, but the professor goes through steps so quickly you are constantly pausing the videos, going back, trying to do what he is doing, not necessarily understanding why, sometimes he doesn't even mention a step which may cause your code not to run, etc. Because Android SDK/Java is so complicated, for a beginners class, the instructions need to be flawless. And they aren't here. OTOH, I have a hunch other MOOCs may handle such a class even worse, so I finished this class. We'll see when another slightly less highly ranked university (Maryland) offers a similar class at the end of January.
From my experience, most free entrepreneurial business classes are trite and often not worth your time. So I did not have high hopes starting this class. That I'm giving it 2.5 stars is actually a good thing relative to most of the business classes I've taken. Given my low expectations, I expected to drop this during the first week. However, after a week, I am still staying in this one because there is some value for me, since I already have a Big Idea and am trying to refine it and find better ways to explain it. The very structured and sometimes too obvious course, does give me some questions to evaluate that are worth asking. I am not convinced this course is good for someone just starting out. The quizzes in particular seem to be the all-too common brain dead variety that either ask you something obvious (and have at least some answers clearly being wrong choices) or they ask you to regurgitate something, that is not important to memorize (or possibly even know). If you are good at English, I highly recommend speeding up the voice on the videos (easy to do because it is Coursera). The professors deliberately talked slower (not just because they are from the South ;-)) so that people who have some challenges with English listening comprehension can better keep up - not a bad strategy for the professors. If you don't do the project and just take the quizzes to get a certificate, then this class is a waste of time or you really have no interest in becoming an entrepreneur. So do the project (even though this doesn't get you any "with distinction" or any other special credential). I wish the course had more examples (including more short interviews like the one it had at the end of week 1). I think real examples of an idea are more convincing then someone proposing their theories.
The material in this course is worth 5 stars. Lots of entertaining and thought/feeling provocative material. I don't need to right much here because it is so obvious from viewing even 1 or 2 videos. Unfortunately the professor's grading/assessment philosophy is worth 0 stars and this is not nearly so obvious. Worse than that, the forums are a battleground with a lot of negative people on them. This is under control of the professor, but I see no indication he is doing enough about it. I have compiled extensive downvoting statistics on 31 MOOCs in a broad range of topics (some quite controversial) and no Coursera MOOC comes close to the amount of downvoting on this moralities class. The forums get a 0 and given that a great value from this class can be discussions with students, that seriously impacts my grade of this MOOC. If you still insist on enrolling in this class (because the videos and reading material is so excellent), my recommendation is to download the material, skip the absurd quizzes and then unenroll. Back to the grading: The professor seems content that half the class fails. This was made clear in two of the three largest threads in the class during the first two weeks. In 50 odd MOOCs, 80% of them on Coursera, I have only seen one MOOC that was harder to pass the weekly assignments (pass means you are on target to get a certificate). That MOOC was done that way because the necessary material actually is hard to learn. Memorize obscure names. You get one time to take the quiz no matter what technical failures you encounter or that no Coursera class that I've taken ever had quizzes with one attempt before his did. No dropped quizzes. He briefly contemplated allowing students to drop their lowest quiz after the first one had such a high failure rate, but after getting a bit of anecdotal evidence in a BRIEF obscure message in the forums, he decided he had enough non-scientific evidence to back up his preconcieved theories and went on with the make it harder than any Coursera MOOC. Machoism. Finally, the threads discussing the quiz style/grading policy were 2 of the three most popular threads in the forum. After the 8 hours when the professor made his decision, one of those continued being very popular with lots of people arguing for a position that the professor decided against. The professor closed this thread which has the practical effect that far fewer people will be able to learn of his decision to go against the popular wishes of the class. This course left a bad taste in my mouth so I dropped it. But you may not care about the grading,or actually like that challenge, and have a tough skin to deal with the forum battlegrounds, so you can enjoy great lectures with no worries. The choice is up to you. Just go in forewarned.
Having previously taken 2 Open2Study courses that I didn't like, and knowing another person who has taken a dozen or more of their classes and not being impressed, I was not planning to take another. But this friend said their Chemistry class was the best of the Open2Study courses she's taken. So I signed up because I wanted to learn a little Chemistry to simplify Harvard's excellent science of cooking class. I can tell it is definitely better than the other Open2Study classes I've taken. The explanations are simple and I don't get buried in memorizing lots of facts. (Though I think the last 1/4 was just a couple algebra equations so I would have liked less material there and more on the reactions... particularly the fun hints about chemistry you can do at home). I liked the professors fun story/example of mixing liquids in surprising ways. In general he has a bit of humor and is not boring to watch. But I won't say that this is a great course. It is worth the time you spend, but if you want in depth knowledge, you will need to take one of the chemistry courses on Coursera or Open Yale.
I agree that this is a lightweight course. They dropped the peer assessments for the 2014 version. Georgia Tech is not a significant college when it comes to psychology and I felt like I could learn similar material (but skipping things I don't care about) just as easy by going to Wikipedia's psychology entry and just wandering through related links.
Unlike the class description above, this class is actually taught in English. Sort of. The class recommends taking the Codacademy HTML/CSS class if you don't already know this. I recommend finding some other method as that course is not good. I'm not keen on learning LINUX or LINUX-based tools. The installed software needs LOTS of tweaking. It is so bad, the professor extended the week for software install to two weeks. The instructors tried to save money by not having a centralized location for this software (they rely on bittorrent) so they have no way to correct the many bugs discovered in it and users are are expected to hunt through the forum messages to figure this out. Unfortunately, there is not a lot of help here. The installed software is also in German, so there is more twiddling with things back in English like it should have been. I got fed up with the course due to the forums and all the bugs.
If you are completely new to having a business, I suppose this MOOC could be useful. But if you have significant business/entrepreneurial experience, this MOOCs value is questionable. The professor spends too much time on obvious things and his words/minute rate is low. Even speeding this up to double speed means the value/minute of his lectures is quite low relative to other MOOCs.
Coming from one of the top colleges in the world in this field, I expect much. So far, I'm not disappointed. The lectures take a somewhat nonstandard approach in having many different people, talking not as sole lectures, but instead sitting at a table talking to the main presenter in the course. It is a little bit artificial,but not over the top like in an infomercial. The lectures are not highly inspiration. This may be due to this conversation format. Or the format was made to compensate for individuals who are not inspirational. I detect the midwestern earnestness typical from NU professors. So don't expect excited, fun-loving presentations. Instead, the course is focused solely on improving the actions you take in business. That being said, the information being delivered is important, high quality and focused.
I have to agree with the first reviewer about the quality of this course. It is quite irritating to listen to the lecturer stop and go back, get lost in which slide he is in, insert way too many ums and pauses, etc. He could learn how to edit and retape his audio. All the long-winded theoretical talk is quite boring. I tried hard to soldier on to complete this course, just for the sake of completing but couldn't take the professor any more so I dropped it.
There is essentially no evaluation in this class. It might as well be a series of YouTube videos. I am usually disappointed by education MOOCs, so to be charitable, I can say I've taken far worse education MOOCs. But I expected better coming from the University of Washington's education department. I preferred the University of Virginia MOOC - Effective Classroom Interactions (Supporting Young Children's Development) for this subject. For older children, Teaching Character and Creating Positive Classrooms is a much better MOOC. Still, some of example classroom interactions in the videos are worth watching. This course takes little time, so perhaps it is worth that.
This class should be called: "Introduction to my disorganized world of Data Science and the hidden grading system" This instructor should be ashamed of himself. It is one thing to have a lot of mistakes in the first iteration of a course (assuming he has never taught this before, outside of a MOOC). But I'm taking this course the second time and there are still major mistakes in it. Although the professor is from a world class university in Seattle, a city with the highest reputation for customer service anywhere, this professor shows disdain for customer service. Poor descriptions that make an assignment IMPOSSIBLE to fulfill are corrected by a TA, buried in some thread, but NEVER corrected in the assignment description, even after a week. Other missing information stays missing for months. The "real world" assignment was using this "not ready for primetime" website Coursolv which mostly seemed to be projects looking for people to do grunt work (nothing remotely resembling data science) for free. The big data assignment (using TB size data) seemed to require that you like Linux in order to figure out how to do it. They even warned you that you may not get through the setup/installation if you use Windows. What arrogance. 90% of the world is using Windows, even if this professor apparently dislikes it. The peer review assignments gave no indication (or gave contrary indications) on what rules people would use to assess you, so you could waste your time doing things that actually took points away from you. I got a 56% on one peer assessment, which is FAR lower than any peer assessment I've ever had in the 50+ MOOCs I've taken. The only 2 things I got out of this MOOC was realizing what I've been doing for decades was called "data science" (so I have a title "upgrade") and by having a mandatory assignment using kaggle.com I finally got myself to try out kaggles (which are cool, but you don't need this MOOC to find out... just go there and try them). If you can find another way to learn this material, do so. If you are a true hacker and like trying to solve the unsolvable, there will likely be good students to learn from. Much better experience than trying to learn from this instructor who cares far less about teaching than many of the students do.
This is my first completed Future Learn course. The research of the university's nutrition department is rated quite highly in the world. With so many conflicting claims about eating, what food is good for you/bad for you, etc, I thought their research influence was important. I particularly was influenced by one part of the course dealing with the detailed metabolic effects of sugar (sucrose) and fructose. Even though in general I prefer the more structured edX and Cousera platform for MOOCs, I thought this MOOC was a good effort.
I completed all the assessments for this course in one day, while barely looking at the course materials. That does not impress me when that was possible. I don't expect that when a MOOC is on Coursera, which has much higher standards :(
I very rarely take a course that offers no certificates, but this class was good enough and the subject matter important enough that I made an exception. The professor's speaking style is in itself stress-releasing, rare even among the various positive psychology-related MOOCs I've taken. This course takes little time and the value it gives to cultures that are overly stressed is well worth the time.
This was the most absurdly assessed MOOC I've ever taken. It should really just be called a small collection of YouTube videos that are a bit too self- promoting rather than to be called a MOOC. The entire "class" is meant to be done in 5 hours. This certainly does not reflect well on MIT. The material in the brief videos can be illuminating or provocative, but this "course" is way too shallow.
This was my first introduction to R. Since the course didn't take that much time, that was probably a good way to introduce one to R. The further classes in this Data Scientist sequence also use R, which teach one more R, using practical examples. However, the Johns Hopkins Data Science Series MOOCs are mediocre at best, and awful at worst, so I recommend taking other MOOCs that use R (EDX/Texas Foundations of Data Science, EDX/Karolinska Institute Exploring R in Statistics, EDX/Harvard Statistics and R for the Life Sciences, Coursera/Duke Data Analysis and Statistical Inference, Stanford Statistical Learning, EDX/MIT The Analytics Edge, etc.
Pluses: Some of the presenters in the videos are giants in their fields of psychology. The content you learn from them is worth every negative in this class. Cons: The assessment was watered down in the second iteration of this course. I strongly disagree that every student should focus on the particular set of 7 character strengths determined by the course instructor, who is not a psychologist, but more of a fan. This is a subversion of the tenants of positive psychology.
I thought this course would spend significant time on forecasting the societal results of not doing enough to reduce global warming. It didn't. But overall, the content was not bad. I also thought the peer assessments were weak, but since the standards were so low to pass the class, that didn't create a problem.
This was perhaps the easiest MOOC I've ever taken and I learned almost nothing from it. But since it was the prerequisite of all the other 8 MOOCs in Johns Hopkins Data Scientist series, I felt obliged to take it.
I liked learning how to quickly make useful graphs for this class. I'm not exactly keen that R has 3 disparate systems for doing standard graphs (2 would be more than enough), but since I was barely tested on one of them, that was OK. I do think the assessment strategy is a bit odd, where you are not assessed on about half the material.
This course has an odd assessment strategy. The second half of the course material is not tested, and the second project seemed rather simplistic. Still, I highly applaud the goal of literate programming and reproducible research, so I am happy I was introduced to this class. At first I had skipped it to take more advanced classes in the data scientist MOOC series, but then realized it could be useful to take. I'm glad I took the course.
The first half of the class I learned almost nothing since I've taken statistics as a math major (albeit a few decades ago). Somehow I passed this class, but I do not consider that a mark of learning. Don't take this course. Take the one from University of Texas on EDX called Foundations of Data Analysis. Or failing that, the one on EDX from Karolinska Institute (Exploring Statistics with R), or possibly the Coursera one from Duke (though that is a much longer MOOC).
I passed this class by taking all the tests on the last day of the class and barely looking at the material provided by the course. That is a big disappointment since this class was given by Harvard. However, I've heard so many good things about the course, that now that I have time I will look at the actual course materials which I expect to be interesting.
This is an excellent MOOC. It cannot compete with an experiential, physical workshop like Gerald Weinberg's Congruent Leadership Change Workshop, but as this free MOOC costs 3000$ less than that and the teachers of that workshop retired a decade ago, it's the next best option. ;-) As I had to begin the course quite late, I look forward to taking it again this fall when it is offered again. I do wish they had left the materials open to view after the course ended.
After passing several quizzes with 100% after not looking at 1 second of videos or reading any materials for this course, I was tempted to see if I could get a 100% for the entire course that way. But even that little time was more time than I have to give for a class that is teaches so little. The only reason I gave this 1.5 stars vs. .5 stars is because a friend said she thought the videos were interesting or maybe because she thought the professor is cute. It wasn't worth the time for me to look. I'll cut the prof some slack since this MOOC comes from "Germany's finest university", but I remain underwhelmed by that label.
Having passed Stanford/Coursera's Machine Learning class and having done quite a bit of work before running out of time in Berkeley/edX's Intro to AI course, I was looking forward to seeing Sebastian Thrun's approach. It is a good compliment to those other two. Unfortunately I only got a third of the way through the course before Udacity went to the pay model for its MOOCs, so I didn't finish it.
The Johns Hopkins Data Science series is a mish-mash of often poorly designed assignments and typical last-century style lectures. This class is no different. If you want to get the answers right, you will need to spend a lot more time than the advertised 4 hours/week unless you are cheating/gaming the system or already know this topic. The quiz questions are often poorly explained, so you'll need to look at the forums to figure out what is going on. The professor is 100% vacant from them, and there was no TA present at all either. Given the problems with the assignments they created, this is inexcusable! They are trying to run all 9 Data Science MOOCs this month, so the staff is spread too thin. The bright side is that by struggling so much trying to figure out how to answer the quizzes and project, you will very likely retain that hard-won knowledge longer, assuming you don't drop the course out of frustration with its poor implementation. In medicine, there are only a few institutions in the world at the level of Johns Hopkins. Unfortunately that is not so with their computer science department and I can imagine their actual courses even in that department are far better than the MOOCs they put on at Coursera. I would think their administration (and marketing people) would not be happy if they saw the Johns Hopkins brand being sullied with such poor courses that are widely available because of the Internet. I only give this class a 2 because at least the professor isn't as poorly organized as the one teaching the Regression and Statistical Inference classes. I only continue in these courses, because it is a way to get me to learn this material better (and I'm almost done with all of them). If you have the option to take better courses in Machine Learning/AI/Data Mining (i.e. from Stanford, CalTech, Berkeley) take it and skip this.
Given that a quarter to half of the time spent in business intelligence/data science projects is spent on ETL (cleaning data to make it useful to analyze) this course topic could have a wealth of information. I've spent many man years doing such work, but wondered if this class would teach me something new (particularly with regards to getting data from the Internet). Nope. However, there is a caveat in my "easy" rating for the MOOC: As others hear have noted, the assignments/quizzes are extremely poorly worded. Like with the other mini- MOOCs in the Data Science Series, if it weren't for the students (and community TA) on these courses, nearly everyone would give up at a much higher rate than is typical for MOOCs. Either you will spend a MUCH larger time than advertised trying to figure things out on your own (which will give other benefits if you are new to the topic or R, if you have the patience), or you go on to the discussion forums because invariably others have the exact same confusion. I have pity for the people who've paid significant money for these courses.
I took a couple quizzes, passing them with 100% despite not looking at any of the materials. Then I looked at some videos. Then I dropped the class. This class is a waste of time, with even lower standards than the typically low standards of MOOCs about education.
I find the standard course materials very interesting and the list of optional readings is so long it might take me a year to wade through them all. The peer assessment templates make it much easier for people to do a better job on peer assessments. The class is also experimenting with some software to make this much better (PeerStudio) but I'm not sure this tool is ready for prime time. But at least they are trying. Nearly every education class on Coursera now and in the future seems to have dropped the free statement of accomplishment offer and this one is no exception. At least one non-education class has also done that. So I don't know if it is appropriate to single out this class for punishment based on that. I like the extra work the professor has done to make even the interview videos more memorable. After the interview is done, she inserts images into the videos, related to the words the interviewee is speaking about, to build connections to the concepts. The quizzes and final seemed fairly easy.
With the wealth of new MOOCs starting in September, it is hard to justify taking this class. I looked at the first handful of videos and determined that this course apparently is targeting people who have little experience with video games (i.e. people over 60). I suspect it is way too basic for the rest of the registrants. It was for me, so I dropped it.
OMG is this professor boring. She seemed to be reading verbatim from her notes. Her voice never showed any excitement whatsoever and the material seemed really basic. Her face barely seemed to move. I watched using the Coursera Android App which doesn't have speed up. I'll try skipping to some topic that is more interesting, run it on double speed on my PC and see if it gets any better. Otherwise, I found a MOOC to prune from my list. OK, I tried that and it was still boring. University of Amsterdam has a MOOC just starting now that covers the same area, so hopefully that will be better.
Interesting history class about a topic I know almost nothing about. I've only done the first 1/6, but I like how they describe the history from the point of view of a half dozen every day people. FYI, like all FutureLearn MOOCs, you have to pay a moderate fee (24 pounds) for a certificate. In this course, you only need to do 1/2 the readings/videos/discussions and *attempt* all the quizzes to qualify. That seems like a pretty low bar for a MOOC.
One word review: Meh. This is only a 5 week course and the first week of it was very basic and not all that interesting. If a story isn't interesting at the beginning, you generally don't read further, flip the channel, move on to the next webpage. I did the equivalent and dropped the course. Storytelling for a Change now running on the NovoEd platform looks like a better choice, though I wish they would run the Storytelling MOOC on the Iversity platform again.
This is an excellent class that I watched the videos did all the quizzes on, but had to stop work on the rest of the assignments due to competing demands. I am taking the 2015 iteration. My main complaint on this version is that the course materials don't seem to have any updates a year after the last iteration.
This is a practical applications course. If you want to learn WHY things work the way to do to better remember and understand them (i.e. learn the fundamentals), I recommend the Linear Algebra Foundations and Fundamentals course on edX from UT-Austin. In my view, it is probably best to do both courses. Alternatively, maybe Brown's Coding the Matrix is a good one course compromise. The assessments are too easy. So if all you want is a good grade, you will be spoiled here. But I recommend playing with the R code examples so you learn more that sticks after you finish the course. The instructor's delivery is OK, but he seems quite knowledgeable. It's a very short course, and you can finish it any time within the 3 months after it began.
The other reviewers are right. Jeffrey Ullman is a poor lecturer. That is apparent in less than a minute of watching him. I'm trying now to just read the transcript and look at the slides so I don't fall asleep listening to him.
Unlike the previous 14 reviews, this is about the second iteration of the class. From what I can tell, the professor has made a fair amount of changes addressing some of the complaints in the other reviews (and the 14 reviews averaged 4 stars, so the complaints aren't that major). As this is only my first week, I set the star ratings for content and instructor are set to average until I can better assess the course (and whether I need to look at any videos or not). I've taken python and linear algebra MOOCs before, which is good because this class takes a lot of time to do well in. I see that the professor has upped the time estimates from 4-5 hours/week in the first iteration of this MOOC to 7-10 hours per week for this one. Maybe 7-10 is OK if you want to get 60% on every single assignment (a requirement for a certificate), but if you want to shoot higher, most people will need even more time. I'm only finishing up the first week of assignments, I've watched no lectures and I'm guessing I'm up to 15+ hours. I like that a community TA has set up a thread for each problem in the assignments. An even better improvement on that would be to also include a link on the assignments page to such a structure (e.g. the Pattern Discovery in Data Mining MOOC on Coursera has links on a weekly page which lists each video and a button linking to a subforum for that video). If you want to be able to get a certificate while missing or not completing most of some assignments, you are out of luck. I've never seen that in a MOOC before. Since I want to do very well in this course, I'm biting the bullet and spending a lot more time than I had planned, to do this. I think for MOOCs which are taken mostly by people who are non-full time college students, the professor should split this up into multiple MOOCs so he can lengthen the course time and reduce the weekly work load.
I have tried to take this a couple times now and have always been too busy, but since I'm making a huge change in my life over the next couple months, I figure now I will really complete the course. The "community" track of this course relies on peer review, which often scares away students who've taken a MOOC with peer reviews. However, one thing that impresses me, from a teaching style, in this MOOC is that it gives examples of what a good essay is like (the only other MOOC I've taken that had this is "Learning How to Learn"). Besides teaching you something, the essay examples also greatly lessen the fear of students incorrectly giving you a poor peer review. The peer reviews also have a minimum word count requirement, so you also don't spend a huge time on an essay, only to get a peer review with numbers and no words or barely useful comments like "That was nice".
If you have taken any R or statistics before, this course is not worth your time. It took me only a handful of hours to "pass" the course. OTOH, if you haven't done either of those, it is definitely preferable to the Johns Hopkins courses. This course is uneven and short. It starts out with pretty basic stuff in R (if you even have a little experience, you can just skip all the material and just take the quizzes). The 3rd week it starts getting into stats, and then quickly jumps to more advanced material. In my opinion, the jump is too quick, they want to do too much in too little time. At least with the Foundations in Data Analysis EDX MOOC from Texas, there was better pacing.
I had a great time working on project assignments with my team for this class. Much more fun than learning this by oneself.
I have at least one child with reading/learning disabilities (including ADD) so this course was more than something of academic interest to me. That it was sponsored by one of the world's top 3 education schools made me feel much more confident that I wouldn't get advice that would be contradicted by mainstream opinion now or next year when the next research article came out. As there is no other MOOC anywhere discussing this topic, you really have only one choice unless you are going to sign up for actual college courses, and even then I would only recommend doing so from a university at this level of expertise. My only complaint was that I wished there was even more diagnostic tools provided, and particularly, some for languages other than English as my children are natively bilingual, but their reading is primarily in a language that is not English.
This class had much hope, with the promise of select students getting to go to a retreat/mini-incubator. But it was sadly, a waste of time. The practices advocated by the professors may be suitable for Fortune 500 companies doing the same old same old, but not for innovative social entrepreneurs. The only thing differentiating Fortune 500 practices in this course were the things you would do to get rich foundations to give your never-make-a-profit idea money to burn. Notably, there was nothing about testing ideas out on potential customers/creating some sort of mockup/prototype. Silicon Valley would laugh at such a course. At or around the same time there were 3 other Social Entrepreneurship MOOCs (1 on Coursera and 2 on Iversity). All could use a good dose of Silicon Valley realism, but the closest to breaking the decades old business practices was the Social Entrepreneurship MOOC from Copenhagen. As it is being run again in April 2015, I recommend that one over the other 3, but be sure to take Steve Blank's Startup MOOC on Udacity (which is always available) first.