- 13 reviews
- 13 completed
This course provides a good introduction to both the social networks and the game theory (it has a little bit of both). It's more qualitative than quantitative, in the sense that there aren't many technical challenges (or at least there weren't in the first version of the course, which I have completed), but the student receives a substantial overview of the field and learns some essential vocabulary and relevant concepts, which can serve as a starting point for exploring these topics further. Prerequisites: Good command of English and high-school math.
As was already said on this site, this course is a great follow-up to the Machine Learning by Andrew Ng. The material is more advanced (specifically for me the Restricted Boltzmann Machines were a big surprise, I have never heard this term before) and you need to do a lot of own study to be successful in this course. The quality of the material, both the video and the lecture slides, was quite good. I only wish there were more links to the related research and/or books. Of course, this is one of the courses which might leave you with the idea of how little you know about the subject after all, but this is better than the illusion of full knowledge :) Prerequisites: some programming experience, math on the undergraduate level. Previous exposure to machine learning helps to lower the amount of new information and to focus on the novel ideas.
This course grew up on me. In the beginning, it felt simple, but as time went, the lecturer proved to be very knowledgeable and his approach to the topics was very thorough. Long time ago, I have learned that period of history from a completely different point of view, and now it was interesting to "compare the notes", so to say. I liked the "holistic approach" in the sense that the course really tried to show how the global tendencies manifested themselves in different parts of the world and to find the similarities in the development of very different countries. In general, this was one of the mind-broadening experiences. I am glad that I sticked with this course till the end! Prerequisites: English language is a must. Some previous knowledge regarding the period in question would also help, otherwise the amount of new information might be overwhelming.
One of the best philosophy courses I had through Coursera so far. It introduced me to several new names in the "modern and postmodern" domain, for which I am quite grateful. The lecturer was enormously engaging. If you want a proof that philosophy is an inspiring subject and/or want to understand which way the "thinking about thinking" went during the last couple of centuries, consider spending some time on this course. If there will be more courses with the same lecturer, I am in! Regarding the prerequisites: good command of English is a must, previous exposure to philosophy would also help, because it provides a base from where to start, but taking into account that the modern period, in a way, "began from scratch", you might want to give this course a try even if you haven't studied philosophy before.
Great course and a must for a professional coder. It helps to understand how the programming languages work by taking you through all stages of writing a compiler, from the code parsing and lexical analysis to the generation of the machine code, and exposing you to the theory behind these stages. The only regret I have is that I couldn't spend more time on this course due to circumstances, and the very last assignment was quite time consuming. I did earn enough credit for completion, but I would still redo this course if time allows. One of the most technically challenging, yet very rewarding experiences!
Great course - a lot of material covered. If it will be offered again (I wish!) the advice for those who wants to take it is to have the book as well (either the recommended one, or a free Introduction to Information Retrieval, written by Manning et al http://www-nlp.stanford.edu/IR-book/ and to dedicate quite some time to this course, especially if you haven't been involved with NLP before. Programming experience is a must (the first offering used Python and Java), as well as some exposure to the probability theory. I have been going through Probabilistic Graphical Models at the same time, and these two courses slightly overlapped, though NLP can overlap with almost everything in Computer Science. All the assignments were using English texts as data. If you are interested in the automatic translation, have a look at another, more involved NLP course: https://class.coursera.org/nlangp-001/class/index . For most of the other NLP-relevant topics the course of Zhurafsky and Manning is a great starting point.
The course provides an overview of the topics which the modern sociology considers interesting. It also clarifies what can be considered as scientific approach in the sociological research. The readings which were required for this course were on the serious level, and the students had to write essays based on what they have read. (This was one of the first experiments with the peer grading, I think; I took the very first version of this course). Also, there were regular "live sessions" which included not only the Princeton students, but some of the MOOC learners. In other words, the course looked very much like "the real one". The professor was friendly and with a good sense of humor, combined with a substantial knowledge of his subject. As a result, the lectures were engaging and informative. Various aspects and problems of the social life were touched. Many of them were related to the American society in particular, but on the forums people were discussing how the ideas from the course could apply to their own communities. The interest and the level of participation was high, and I think this course was a big success. Would definitely recommend this course as an introduction to the subject.
This is probably as abstract as it can get in CS (which is by itself an abstraction). The most relevant analogy from the humanities might be a course in epistemology. In other words, this requires some heavy thinking. The written course materials were of great quality, very carefully prepared, and there is also a book for those who want to go deeper. Actually this is almost a must, because it's one of the subjects where the lectures can be understood better if you did the readings first. Don't expect an easy entertainment from this course, but if you are interested in the theoretical basis behind the modern computation and are prepared to invest some time into the learning, then give it a try. A substantial exposure to the formal thinking (theorem- proving and the logic in general might be more relevant here than the actual programming experience) is a prerequisite for this one, you won't go too far otherwise. I am very grateful to Prof.Ullman for having the trouble to offer this high-quality course as a MOOC. For the software development practitioner, it's a good opportunity to look into the depth beyond the familiar concepts. It also helps to understand what the Computer Science is about. At the very least, you will find out what P=NP means! :)
I liked this course because it provided a serious-style overview of the modern cosmology. I have graduated as a physicist, but have been working as a software developer for the most time afterwards, so there were quite a few topics to brush up for me. You definitely need a book for this course (one of those recommended) and some time to set aside for the self-study (in general, the science courses aren't the ones where the lectures will be enough - they are to be seen as a guidance!) I wish I could get more involved with the subject! This is one of the most interesting (even though also the most unrelated to the so called "real life") things we, the humans, are trying to understand, using whatever understanding we currently have. Can't help wondering how many of these concepts will survive after another 20-30 years!
One of the most technically challenging, but also one of the most interesting courses I have taken. Loved the subject, hated that I could not spent more time on it. The book (which I bought) helps a lot, if you are serious about the subject, I recommend getting it. This is one of the subjects where the lectures aren't enough, they can at best serve as a guideline and the study effort is yours! Regarding the prerequisites: some knowledge of probability theory and of programming is a must. Previous exposure to Octave/Matlab might help too.
Nice course, enthusiastic professor. He put the ancient mythology in more broad prospective, connecting it with the anthropology in general and the existing theories of myth and its role for the human societies. This might sound dry, but the course was very engaging and easy to follow, due to the enthusiasm of the lecturer and the well-prepared course materials, reading recommendations, quizzes and assignments. This is one of the courses which can help you to become a better thinker, or at least to get the opportunity to think about many aspects of life which are now taken for granted. I would recommend this course to anyone who wants to learn more about the roots of our culture.
Great course! I love literature, but didn't have a lot of exposure to the American poetry before (excluding Emily Dickinson and a couple of other names). I learned many new names and had an opportunity to get a bit of insight into the historical context behind their work. The relaxed way in which the course was taught (the professor was discussing the course subjects with his students, which is more engaging than a monologue, especially with a topic like poetry), the challenging (in a good way) topics for the essays and the friendly community of the co-learners, all combined, made it a good experience. Also, I might be taking this course for another time after a while, especially if there will be some new names in the syllabus.
That was one of the first courses I took. I am a software developer who moved into the field from physics, learning most of the necessary skills on the go. Even though I already worked with databases, the systematic course like the one Prof. Widom taught proved to be extremely useful, because for me, it added some missing links between my existing knowledge of the databases and the theory behind them. I would recommend this course to anyone who is working with structured data and feels that he/she needs more background knowledge.