- 20 reviews
- 17 completed
Great videos where Professor Sandel engages with his students very interactively. The course is mind opening, and its material should be compulsory for everyone. There's a fair amount of reading, but you can do without it. Even if you don't take the Quizzes, I really recommend watching all 24-minute videos.
After "Moralities of everyday life" I wanted to dig a bit deeper into the topic of ethics, and I think this was a great course, which actually needs no prior knowledge. I didn't get into doing the assignments, so all i can say is that the videos are informative, engaging and thought provoking. I even found in Singer something of a personal hero. The course is about what is ethical or not, but more importantly about how can we define what is ethical, reviewing all sides of the story.
The course is a comprehensive review of contraceptive methods, and includes best practices for guiding people in choosing their contraception methods. Even though the lectures where not terribly engaging, the course is very informative, well prepared and correctly presented. The weekly quizzes had a few errors (like any first run course), and the two writing works where according the material given. I recommend it to anyone wanting to learn a bit more about the contraceptive options available; I've learned a lot, specially regarding changes in the area in the last decade or so.
Great introduction not only to Greek and (to a lesser extent) Roman mythology, but also provides insight about methods for analysing any work in terms of psychology, dichotomy and functionalism. Weather you read the Odyssey or not, the analysis given to that work alone is worth taking the whole course.
Great course about ethics based mainly around moral psychology. Professor Bloom ties ends between evolutionary psychology and social imposed ethics, and has a ton of very interesting experiments' results. Its a nice complementary course to "A Beginner's Guide to Irrational Behavior", which is more focused on behaviour than moral decisions in particular.
This course didn't work for me. The presentation are not well prepared, professor Bailey is really not engaging and delivers the videos in a monotone and unclear voice. The material is also very basic and not very interesting. Hope others will be able to get something out of it.
The course touches probably all the most imperative problems currently looming us throughout the world , and partially looks at possible actions to mitigate these problems. The content is somewhat introductory and disorganized, and is not complete, but some important players and ideas in the area are presented.
Disclaimer: I just watched the videos and did the surveys The course is a great introduction to irrational and biased behaviour. The videos are very engaging, and even though sometimes a bit repetitive they give a lot of information in a very digestible way. I recommend it to people from any background wanting to understand human biases in order to make more rational decisions.
Don't be fooled by the title. There is of course history, but you'll get also evolutionary biology, psychology, and more, from a point of view not just for humanities. The course opens your mind to question yourself all pre- conceptions by studying the history but also the drivers of humankind in order to abstract yourself from present concepts we take for granted. Biological, religious, and moral convictions are studied with the main changes in the path of humanity in a very intuitive and intelligent way. The professor also presents several points of view, trying to make you think, investigate and make up your own. The course is very easygoing, with no written assignments and very simple exams making it more like the Carl Sagan TV series of human history.
The course covers a whole lot of information, so it doesn't go deep into any of them. It is nevertheless a very nice introduction to Big Data, and some of the programming assignments are very interesting, and none is particularly hard. The lectures are best viewed at 1.25x, but you quickly get used to it. I recommend it as a wide introduction to Big Data.
The course was very well structured, though I felt there was too much emphasis on evaluation tests (yet very useful in real life). I also missed some more advanced content-based methods, though other courses touch the topic in depth. The programming exercises were in Java using the LensKit library with half baked projects. That made it easier to focus in the logic of the problem you where trying to solve, but took you a step back from understanding the details of constructing a system yourself. All in all, I think the lectures are very well thought of, they cover a whole lot of useful information, they include interviews with industry big names. The course requires quite some time to do the programming and written exercises, and the exams are far from trivial, so be prepared to invest quite some time in the course. I highly recommend it to anyone interested in the topic, or thinking about implementing a recommender.
Very interesting view of the biology side of food, and the chemistry behind cooking. The course starts with food and senses, and moves to the reactions that take place during cooking, macerating, grilling, and other cooking procedures. It might be a bit too much if you are not into both science and cooking, but definitely a good guide to understanding what's going on in the kitchen.
Having worked on the subject for a couple of years now, there is very little new I took from the course. It relies on proprietary software (ArcGIS) instead of the many open source solutions, mainly due to its web availability, but I found that to be a down side. Anyhow, the course is quite basic and light, and can be a great way to see if you like the subject, and start managing the vocabulary and basic notions of GIS, maps and cartography.
The course was very disorganized, without clear passing conditions, and suffered changes along the way. Yet the content was very good as an introduction to data science, and there where some really interesting assignments such as matrix multiplication in SQL, or the Kaggle competitions. Overall, I think I took a lot of good things from the course, and I recommend it to anyone interested in the topic, provided we have enough self motivation to overcome the course's shortcomings. Hopefully any future iteration of the course will be improved.
The course is a really good introduction to Machine Learning with practical work and very well prepared expositions. Highly recommended.
The course is very basic, at least for my taste. The guy speaks clearly and is engaging, and the topics are presented first simply and then more technically, so it might be interesting for others.
I dropped off around week three in favour of other more interesting courses. The lectures where not bad, and the assignments were in good correlation with what was explained, but the course failed to gain my interest. The overall content was rather bleak, and could have been explained in a one hour video. Perhaps if you don't even know what Unit Test means this course can be a good introduction to testing that goes down to fuzzy testing, which is theoretically a great idea, but in practice is very seldom used. I'm also not very satisfied with Udacity's interface, specially after using edX, but perhaps that's more of a personal choice.
This is, hands down, the best on-line course I've taken so far. Maybe it's the first-love effect, since this course first introduced the great interface now being used by edX, or perhaps because I really felt I learned a very difficult load of material driven by the thirst of green ticks. The lectures are long but very interesting and the exercises are challenging and engaging. The provided book is also very good, and a rarity in on-line courses. Finally, the virtual laboratory was just simply great, and the forums even better than the current edX. But the course is not for anyone; there's a lot of math(differential equations), and it takes a lot of work to pass it. Nevertheless, it is definitely worth it and I strongly recommend it with a 5/5.
The lectures are easy going and self-explanatory. A lot of mathematical and simulation models are presented that make for a great toolbox for the modern programmer. There are a couple of easy demonstrations, but in general the concepts are explained very clearly and perhaps shallowly. There is also no practical usage of the gained knowledge, which was a bit of a let down, and the exams were quite simple and short. Perhaps having less models and giving some projects to implement them in real time situations would end up requiring more effort and cover less material, but would have had a greater educational value. In any case, the course deserves a solid 4 as an introduction to the subject, and is highly recommended to anyone with some curiosity.
This is, together with MITx 6.002x: Circuits & Electronics, the best on-line course I've taken and completed. The lectures are clear and entertaining, the homework inviting, and the three projects where engaging and simply fun. I'm a programmer, but didn't know much Python. I don't know how hard would it be if you knew no programming. You can make it through the course with less week effort than what's recommended, but It was a pleasure to invest time in the projects, so do try to make time for it. This is the first part of a two-part course. It had a great balance between theory and practice (though I was missing some proofs now and there) covering everything from start to Q-learning,, but there are still a lot of things left out. I'm hopping part two goes down to 'deep learning'. All in all, a 5 starts course.