- 11 reviews
- 10 completed
The first session of this course was a mess. The content was not well explained and there was little quality control. The lectures were brief, which normally is good, but in this case they were too brief was we could have used more explanations. The lecture quizzes were surprisingly too easy. I dropped the course after 2 weeks because I couldn't figure out if it was my fault or the lecturer's fault when I couldn't match up his words with the math symbols.
This is the worst MOOC I've taken so far out of about 30 I've dabbled with. First, the title of the course has little to do with the course content. There is no strategy involved at all. There are no management-related issues at all. I would have called this course "Mental Models: from Philosophy to Creativity". Second, the writing assignments were very poorly written due to the staff's poor command of English. There was so much ambiguity every week that students were complaining profusely in the forums. When you graded assignments, you realized your peers had 2-3 different interpretations of the instructions. Hopefully, they'll be fixed in later sessions. The only reason I stayed with the course until the end is that it is easy and doesn't take much time, and I found the discussions of philosophy and inductive vs. deductive reasoning interesting. But in the end, I learned very little.
Great course, packed full of fascinating knowledge. I recommend this course to everyone, as you'll learn a lot about how you think, feel, and behave. The lectures are very engaging, the quizzes and exam are easy (and a bit silly), the two writing assignments are interesting. The required readings, which mostly consist of research papers, are a bit dense and more challenging to go through but you can easily get away with just skimming them as you take the related quiz.
The class was interesting but the quizzes and final exams were annoying. There were a lot of problematic questions: \- complex questions: you'll see very confusing wording \- unimportant questions: "Who came up with X? \- tricky questions: "Which of these are false?" You may often misread the "false" because it's not emphasized And you're not given the answers to quizzes and the final exam after the only attempt that you get.
This course was so-so. As with many self-help books or courses, you may learn a few things and you may end up with several tools for improvement. But you may also leave this course with a feeling that you've just watched a fancier version of a Tony Robbins video. The instructor likes to give silly names (e.g., Intentional Change Theory) to simple things that are either common wisdom or ideas that you've seen before. The idea that you'd have to take an in-person "graduate-level course" in order to advance beyond this course is just silly (need a Bachelor's Degree to do self-help?) and makes me think that Case Western Reserve University doesn't belong on Coursera alongside serious institutions. It's interesting to see the parallels between this course and another Coursera course, "Better Leader, Richer Life"; both courses have engaging lecturers who are deeply convinced that they have a unique system for self-improvement.
This was an interesting, enlightening course. The lectures were engaging, the problem sets and final were fairly easy. I'm glad I took this course and I'm signing up for the follow-up Advanced Competitive Strategy course.
Note: I only watched the lectures and didn't do any assignments or participate in the forums. I think that class is groundbreaking. I found the lectures very interesting and reflected and expanded many of my own thoughts in the common area between meditation and psychology. It was great to see someone start the conversation in a field that I believe should be researched much more extensively. Many of the ideas in the course are Robert Wright's own. You might feel that most of them are hand-wavy. You'll often hear "so it does make sense that..." But that's to be expected. In a sense, this class is like philosophy. Some of his ideas, you can be ready to accept, many you'll have to designate as contrived. The lecturer is quite engaged in the forums and loves to record office hours addressing many of the students' questions.
As usual Prof. A's lectures are great. She's engaging and I love the simple way she explains concepts. The assignments and exams are of high quality. They really make you think and any mistake you make is very instructive. There is one thing that is particular difficult about this course: there are a lot of concepts that are similar to one another and it's hard to differentiate between them. I had to re-read book chapters. And I may even re-do this course next time to re-watch the lectures. Of the 3 courses Stat2.1x, Stat2.2x, Stat2.3x, this seems to be the toughest and most time-consuming (if you want to understand everything).
Excellent course. Well-designed. Interesting lectures and assignments. Relevant Kaggle competition. Lots of work with slightly repetitive assignments. If you follow the course properly, the material is quite easy to understand and the questions easy to answer. You'll feel empowered after this course as you'll have learned quite a bit of R. I would pair this course with the first courses of Coursera's Johns Hopkins Data Science Specialization, especially R Programming, to make the Kaggle competition more manageable.
This class is a good introduction to a wide variety of subjects if you don't have much programming experience. But it's not for experienced programmers. You'll learn simple, brute-force solutions to common science problems, but often you won't learn the canonical algorithmic solutions taught in algorithm classes. And it's not really an introduction to data science -- more an introduction to an introduction to data science. The lecturers are engaging, the assignments easy for those with programming experience. The quiz and final can have very frustrating questions that are ill-conceived. If this class is supposed to be about how to write simulations to measure phenomena, you'll find that many quiz/final questions actually ask you to predict how a simulation would behave *without* running the simulation. This is silly in my opinion as it defeats the purpose of a simulation and the course doesn't properly prepare you to answer these scientific intuition questions (unless you do a lot of experiments beyond the assignments on your own, or maybe read the included textbook, which is not required reading). It's a decent course but I wouldn't recommend this course to any of my friends, as I don't feel that I got much out of it.
Prof. Adhikari is probably the best lecturer I've ever listened to. She explains everything clearly in a way that mirrors your thoughts, doubts, and confusions. The course was of medium difficulty and had a medium workload. The textbook was a bit more challenging to go through than the lectures but were quite instructive. I will be sure to take all her courses.