Web Intelligence and Big Data

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7/10 stars
based on  58 reviews
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FREE

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  • TBA

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Coursera online courses
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with yo...
Coursera's online classes are designed to help students achieve mastery over course material. Some of the best professors in the world - like neurobiology professor and author Peggy Mason from the University of Chicago, and computer science professor and Folding@Home director Vijay Pande - will supplement your knowledge through video lectures. They will also provide challenging assessments, interactive exercises during each lesson, and the opportunity to use a mobile app to keep up with your coursework. Coursera also partners with the US State Department to create “learning hubs” around the world. Students can get internet access, take courses, and participate in weekly in-person study groups to make learning even more collaborative. Begin your journey into the mysteries of the human brain by taking courses in neuroscience. Learn how to navigate the data infrastructures that multinational corporations use when you discover the world of data analysis. Follow one of Coursera’s “Skill Tracks”. Or try any one of its more than 560 available courses to help you achieve your academic and professional goals.

Provider Subject Specialization
Humanities
Sciences & Technology
4721 reviews

Course Description

This course is about building 'web-intelligence' applications exploiting big data sources arising social media, mobile devices and sensors, using new big-data platforms based on the 'map-reduce' parallel programming paradigm. In the past, this course has been offered at the Indian Institute of Technology Delhi as well as the Indraprastha Institute of Information Technology Delhi.
Reviews 7/10 stars
58 Reviews for Web Intelligence and Big Data

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Павел Ширяев profile image
Павел Ширяев profile image
6/10 starsTaking Now
  • 2 reviews
  • 1 completed
6 years, 4 months ago
In general, I was not satisfied this course. I think professors English is very hard to understand for non native speakers. May be it was possible to explain some topics in more simply words. He trying to speak slower in the beginning but it didn't work. The problem is what to speak and not how fast. There is a lot of math formulas in this course and a lot of theory. There is a lot of questions without explanations. This is not what I am expected from this course. But can't say that I haven't learn something new. I have learned a lot, but that was harder than it could be.
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Equanimous Creativity profile image
Equanimous Creativity profile image
7/10 starsCompleted
  • 33 reviews
  • 32 completed
6 years, 6 months ago
I took this class first time it was offered at coursera. I think this class is the hardest to review, because the quality varies from wasting our time with detailed videos on simple things over mindblowing insights into the nature of the subject to advance stuff without any details.
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Dan Wigglesworth profile image
Dan Wigglesworth profile image
8/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 4 months ago
I had very little prior experience with the specific subject of the course but as it turns out, I had LOT of very helpful background (BSc Computer Science and Statistics). This course was similar in many respects to a different coursera course I took. The other course was given by a professor of engineering at Georgia Tech and was heavily math focused (robotics/ control theory). The Big Data course was somewhat less heavy on the math. Both courses were excellent in sofaras they both introduced a LOT of new stuff without being overwhelming. One negative about this course: it seemed to wander slightly off the big data theme here and there which was a little disconcerting... but then again, who am I to say? I'm not the expert! :) I am thinking in particularyl of the very little bit of attention we put on the calculation of bayesian probability (which was very interesting and no doubt related to big data...) and also the very little atte... I had very little prior experience with the specific subject of the course but as it turns out, I had LOT of very helpful background (BSc Computer Science and Statistics). This course was similar in many respects to a different coursera course I took. The other course was given by a professor of engineering at Georgia Tech and was heavily math focused (robotics/ control theory). The Big Data course was somewhat less heavy on the math. Both courses were excellent in sofaras they both introduced a LOT of new stuff without being overwhelming. One negative about this course: it seemed to wander slightly off the big data theme here and there which was a little disconcerting... but then again, who am I to say? I'm not the expert! :) I am thinking in particularyl of the very little bit of attention we put on the calculation of bayesian probability (which was very interesting and no doubt related to big data...) and also the very little attention that was given to quatitative symbolic logic. These little diversions were interesting in and of themselves, but given the nature of the course, I cannot help but think that the time might have been better spent focused more narrowly on the subject of Big Data. Hmmm. Having said that, I am reminded that the term "Web Intelligence" also figures in the title of this course... I guess that would explain these "diversions"! :)
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Student

5/10 starsCompleted
6 years, 4 months ago
This course covers some very interesting and trendy subjects, but the materials are not very good (a bit chaotic sometimes, quite boring mostly) and, from my point of view, the evaluation is not properly carried out: the quizzes and homeworks (and specially the final exam) are not a good summary of the contents of the course, and sometimes are very tricky. Other positive aspects: it is very easy to follow the videos even if your level of English is not very good, as the instructor speaks very slowly. Other negative aspects: you will need a previous background of programming, preferrably in Python.
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Student

9/10 starsCompleted
6 years, 4 months ago
Very well crafted course. Covered almost all aspects of Web Intelligence and introduction to big data technology such as Hadoop. Would love to take some more courses from Dr. Shroff. Thank you very much for such a knowledge packed and interesting course.
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Leslie profile image
Leslie profile image
7/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 4 months ago
Prof Gautam Shroff did an excellent job of putting together this course. He was easy to understand (in terms of accent). It would have been nice if all multiple choice questions (homework, quizzes, in-video) has explanations. A lot can be learned from targeted explanations. I found the material in this course very worthwhile. I had no prior experience in this subject, except I that I know python and I learned sqlite3 in the Intro to Databases course (Stanford2Go). The course took me, on average, 8 - 11 hours per week. I found it useful to transcribe the lectures. There were too many details that I would have lost if I did not do that. The course covered lots of material. Some of it was at a very high level (cognitive science with respect to the way our memory works, overview of big data technologies, Markov models, Graph databases) some of it was in lots of detail, with good examples (Naive Baysian Classifier, Map-Reduce, Logic-deduc... Prof Gautam Shroff did an excellent job of putting together this course. He was easy to understand (in terms of accent). It would have been nice if all multiple choice questions (homework, quizzes, in-video) has explanations. A lot can be learned from targeted explanations. I found the material in this course very worthwhile. I had no prior experience in this subject, except I that I know python and I learned sqlite3 in the Intro to Databases course (Stanford2Go). The course took me, on average, 8 - 11 hours per week. I found it useful to transcribe the lectures. There were too many details that I would have lost if I did not do that. The course covered lots of material. Some of it was at a very high level (cognitive science with respect to the way our memory works, overview of big data technologies, Markov models, Graph databases) some of it was in lots of detail, with good examples (Naive Baysian Classifier, Map-Reduce, Logic-deductive, adductive, inductive). At first I was down in the weeds. But after finishing all the lectures I watched the beginning units again. Then I understood the flow of the lectures better and I saw how the dots were connected. I definitely appreciated the lectures on Machine Learning in terms of Information Theory much more. The second pass through the videos is extremely valuable. This is not an easy course to teach in 7 weeks. It might have been easier to follow if it was just a few technologies. (But that is a different type of course.) This course was about where today's technology came from and how it is evolving and the big picture of technologies, big data, and how it all relates to web intelligence and human intelligence. And how human intelligence can inspire research in web intelligence. The lecture material was hard. The multiple choice questions were mostly straight forward. The programming assignments were relatively straight forward. The final was too easy.
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Njin-Zu Chen profile image
Njin-Zu Chen profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 4 months ago
This course offers a very wide range of topics, and with the limited time that means the in-depth explanations are compact. I found myself pausing and working out some things on paper more than once. I consider this good: you need to do more than lean back and listen. There is a good connection to both practical and philosophical considerations. Overall: well worth the time to get a good overview of what elements are involved in web intelligence, how they connect, and what the current frontline is. The programming assignments are interesting, and push you to actually understand what is going on. They are pretty trivial if you understand the general principles, no need for extensive programs. The assignments are in Python, not something I use on a regular base, and the assignments don't take more than 20-30 lines of code,
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Marco Conde profile image
Marco Conde profile image
9/10 starsCompleted
  • 3 reviews
  • 3 completed
6 years, 4 months ago
This was my first coursera participation and I was very happy with it. The scope of the course is vast, which suits perfectly to me because mostly I wanted to know what is going on with information process technology. It is a course that get you on many of the back-of-the-scene technologies being used to support the internet revolution. This make some people feel overwhelmed by the broad scope of topics, or disappointed by the lack of deep in some subjects. I feel the course manage a very welcome middle point between extension and deep. The explanation on videos are done very slow, which is a very nice feature. My first language is not English and I never had problems following the lectures. This is hard a course for beginners because you should have some notions on probabilities, programming, sql, matrices and logic. Personally I liked the excuse to learn a new language (phyton) and get to know some very nice tools like Orange. I re... This was my first coursera participation and I was very happy with it. The scope of the course is vast, which suits perfectly to me because mostly I wanted to know what is going on with information process technology. It is a course that get you on many of the back-of-the-scene technologies being used to support the internet revolution. This make some people feel overwhelmed by the broad scope of topics, or disappointed by the lack of deep in some subjects. I feel the course manage a very welcome middle point between extension and deep. The explanation on videos are done very slow, which is a very nice feature. My first language is not English and I never had problems following the lectures. This is hard a course for beginners because you should have some notions on probabilities, programming, sql, matrices and logic. Personally I liked the excuse to learn a new language (phyton) and get to know some very nice tools like Orange. I really appreciate the effort to create the videos used in class, because they cover no that easy to explain topics. It was not that easy for me to understand all the topics, but I enjoyed the course a lot. Very recommendable if you are interested in know how the information crunch on internet works.
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Jose Luis Dengra profile image
Jose Luis Dengra profile image
10/10 starsCompleted
  • 5 reviews
  • 5 completed
4 years, 2 months ago
This is a great course, because of its interesting topics and the quality of the most of the explanations. There is a valuable effort in preparing videos trying to be didactic and evolve from slow to fast speed in the speech. This is a suitable approach to the international scope of students for the course, where so many of us don't speak English as primary language. Thanks to this course, I have noticed how uninformed I was about the technology used to deal with data in the web. I am working as database analyst, also with business intelligence, and now I am glad to know about other kind of technologies beyond traditional databases. All the topics have been interesting for me, since I was interested in getting to know about search engines, machine learning, data mining, and how to deal with big data. I have been surprised by the variety of technologies and techniques, as well as the quality of the explanations in the most of the le... This is a great course, because of its interesting topics and the quality of the most of the explanations. There is a valuable effort in preparing videos trying to be didactic and evolve from slow to fast speed in the speech. This is a suitable approach to the international scope of students for the course, where so many of us don't speak English as primary language. Thanks to this course, I have noticed how uninformed I was about the technology used to deal with data in the web. I am working as database analyst, also with business intelligence, and now I am glad to know about other kind of technologies beyond traditional databases. All the topics have been interesting for me, since I was interested in getting to know about search engines, machine learning, data mining, and how to deal with big data. I have been surprised by the variety of technologies and techniques, as well as the quality of the explanations in the most of the lectures, some of them excellent, that make me remember when I was at University. Another phenomen that has surprised me is the great number of people enrolled in this class, and the quantity of thoughts, doubts and help available in the forums, from people from all around the world learning together, something unprecedented in the courses I've done previously. It's difficult to believe that a great course like this is available for free. However I have found some disadvantages: the complexity for some of the topics, some ambiguities and inaccuracies in the language that difficult the understanding, and finally the way that the extra activities are weighted to compute the final aggregate grade, since they don't really help if you have completed all the quizzes so they don't add any extra quantity to the final score.
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Student

10/10 starsCompleted
6 years, 4 months ago
Great course! Good teacher with great explaination style. I would suggest it to all IT students and professionals
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Student

10/10 starsCompleted
6 years, 4 months ago
This course was amazing. It combined theory and practice and taught me about the latest research relating from Markov Logic and Bayesian Inference to Map- Reduce and Data Mining. I also love the philosophical tone that underpinned the entire course.
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Student

8/10 starsCompleted
6 years, 4 months ago
I had no previous experience on this topics, great videos and explanations. Hard assignements from my point of view, but not no-affordable ones
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Sunil Gopinath profile image
Sunil Gopinath profile image
9/10 starsTaking Now
  • 2 reviews
  • 0 completed
6 years, 4 months ago
I actually had attended a training on Hadoop and my current focus is on data analysis.This is one of the very few MOOC courses on data analysis and my first course in Coursera. I felt the course as excellent with great examples to work with but there was lot of complex theory (but lot of pointers). Hopefully ,with the help of this course, i will be able to connect the theory part with practice
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Alfonso profile image
Alfonso profile image
4/10 starsTaking Now
  • 3 reviews
  • 2 completed
6 years, 4 months ago
This is the first MOOC that I have taken and I had some background on Machine Learning (PhD on automatic speech recognition) before I took this course. I got interested because I wanted to learn more about Big Data analytics. On the positive side, I liked that the course doesn't require too much time, it gives an overview of many fields and connects them together, I enjoyed a MapReduce programming assignment and the staff answered in the forum regularly. On the negative side, most of the assignments were multiple choice tests that did not really teach much (no feedback or insight), there were some errata on the material, I feel that from the three programming assignments two of them were a waste of time and I did not really like the approach. Overall I feel that I would have learned more using the time on studying by myself. However, being my first MOOC it is possible my expectations were too high.
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shashank gupta profile image
shashank gupta profile image
10/10 starsTaking Now
  • 1 review
  • 0 completed
6 years, 4 months ago
it is a very good course... i got to learn actually how web is organized.. how it is not just network of pages linked learned about future of web, the semantic web
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Student

8/10 starsCompleted
6 years, 4 months ago
Shallow and wide - lots of topics, both some theories and practicalities, crossing across many domains and problems, and even visiting some latest trends like HTM. The flip side, is that you only know what you don;t know after this course. Which for most of my experience, is the best learning you can have.
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Student

3/10 starsCompleted
6 years, 4 months ago
This course was difficult to understand, partly due to the poor English of the lecturer, and poorly structured. The quizzes and homework were rarely covered adequately in the prior videos. There are many people complaining about this in the forums.
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Student

4/10 starsCompleted
6 years, 4 months ago
For a first-timer in the field, this is not a very good course to take. A lot of very difficult topics are dealt with way to quickly, leaving you wondering about its importance. I followed the lectures and scored reasonably well on the quizzes and homework, but looking at the recap video I get the feeling that I have understood little about the main points.
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Yogesh Kuvelkar profile image
Yogesh Kuvelkar profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 8 months ago
I want to thank Dr Gautam for the great value he has passed on to us. I signed up for this course on Coursera but could not follow the exact course timelines and assignments. Right from the first week lectures I somehow had the feeling that every topic that was being discussed in the course would be a great help later on when you get to the details. Now after completing the course, I am glad to say that I was not wrong. This topic is a hot one for any IT professional. This course has not only helped me to learn more on the core course topics but easily relate with other emerging technologies like cloud, etc
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Robert Komartin profile image
Robert Komartin profile image
7/10 starsCompleted
  • 19 reviews
  • 16 completed
6 years, 11 months ago
[Edit] I have upgraded the rating following course conclusion and recap. In the end, it does provide a well-rounded overview of the field (as well as the materials I was so dearly missing before :-)). Nice in its intention, but failing to go all the way because of: a. the lack of course materials b. the style of "just scratching the surface" - which implies it is good for informative purposes, but hardly enough for doing anything in practice. c. the style of the homework - where students are left "on their own" regarding languages to choose, algorithms to use, basically everything a beginner would need to properly address such a topic.
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Jeanne Boyarsky profile image
Jeanne Boyarsky profile image
4/10 starsCompleted
  • 33 reviews
  • 29 completed
6 years, 12 months ago
I dropped this course at the end of week 6 (out of 8 or 9). What I liked: 1) The *one* programming homework on map reduce. 2) The professors seemed to have an awareness of both in class and online students. 3) The quizzes had some different answers if you retried them. What I was neutral about: 1) Some of the topics were too easy. That's true in some other courses too (I have a degree in Computer Science), but it is easier to skip to the relevant parts. What I didn't like: 1) The English was poor. There were an excessive number of spelling/grammar issues. Some of which affected understanding or quiz questions. 2) Some explanations were fine. Others I had trouble with. If I hadn't taken the AI class (and learned this already), I never would have understood conditional probability from the lectures. 3) Since the class was offered in person too for grades, homeworks were heavily defended to protect the integrity of grades. To the point ... I dropped this course at the end of week 6 (out of 8 or 9). What I liked: 1) The *one* programming homework on map reduce. 2) The professors seemed to have an awareness of both in class and online students. 3) The quizzes had some different answers if you retried them. What I was neutral about: 1) Some of the topics were too easy. That's true in some other courses too (I have a degree in Computer Science), but it is easier to skip to the relevant parts. What I didn't like: 1) The English was poor. There were an excessive number of spelling/grammar issues. Some of which affected understanding or quiz questions. 2) Some explanations were fine. Others I had trouble with. If I hadn't taken the AI class (and learned this already), I never would have understood conditional probability from the lectures. 3) Since the class was offered in person too for grades, homeworks were heavily defended to protect the integrity of grades. To the point where you had no idea why you go a question wrong. (And that guessing/wrong answers were heavily penalized, but I don't care about the grades part.) 4) I was under the impression there would be more hands-on/map-reduce type focus and not so much math/Bayes networks.' Why I dropped the class 2/3 of the way through: 1) MongoDb is offering a class starting tomorrow (https://education.10gen.com) which I'm sure will be more hands on! 2) There was a one week break (school vacation) and I lost momentum. 3) I should have dropped it last week, but was hoping it would get better.
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Sai profile image
Sai profile image
7/10 starsCompleted
  • 14 reviews
  • 13 completed
6 years, 10 months ago
This course covers various technologies behind big data companies such as Google and Yahoo. It puts higher priority on breadth rather than depth. Topics covered in the first 5 units include PageRank, basic machine learning, MapReduce, and storage infrastructures (Google file system, BigTable, etc.). There are 3-4 more units left that will be mostly about machine learning. The course is simultaneously offered to some institutions in India but online students will not get certificate. To me, the biggest downside of this course is that the instructor, who is affiliated with an IT consulting firm, is not willing to share the lecture slides with the students so far, claiming copyright issue or something. That led to some students' voluntarily taking screenshots of the lecture video, compiling them, and sharing them for other students. There was 1 programming assignment about MapReduce (in Python). [Update on Nov. 9, 2012] \- The slides we... This course covers various technologies behind big data companies such as Google and Yahoo. It puts higher priority on breadth rather than depth. Topics covered in the first 5 units include PageRank, basic machine learning, MapReduce, and storage infrastructures (Google file system, BigTable, etc.). There are 3-4 more units left that will be mostly about machine learning. The course is simultaneously offered to some institutions in India but online students will not get certificate. To me, the biggest downside of this course is that the instructor, who is affiliated with an IT consulting firm, is not willing to share the lecture slides with the students so far, claiming copyright issue or something. That led to some students' voluntarily taking screenshots of the lecture video, compiling them, and sharing them for other students. There was 1 programming assignment about MapReduce (in Python). [Update on Nov. 9, 2012] \- The slides were released a week before the final, thus bumping up the rating a little bit. \- The course staff changed their mind to offer certificates to online students. \- There were 2 more programming assignments, one of which offered an interesting insight about how SQL can be used to compute probabilities in Bayesian networks.
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Marek Stój profile image
Marek Stój profile image
4/10 starsCompleted
  • 4 reviews
  • 4 completed
6 years, 12 months ago
Very interesting subject and the approach taken by the professor. However the course is rather chaotic and not well prepared.
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Ram Ram profile image
Ram Ram profile image
9/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 10 months ago
You would be able to understand several components of Big data technology(LSH, Machine Learning, Information theory, Map reduce etc), how they are related to each other and how they fit in to the big picture. The course while giving an overview also helps you get your hands-on MapReduce, Bayesian Classifiers, TF- IDF etc., As mentioned by the Dr.Shroff, the homeworks go deep and test your understanding of the material. Unlike many online courses in this subject, you would have a sense of accomplishment after you complete every homework. If you are planning to build a career in Big data, this course will help you understand where you stand, what are the different paths that you might pursue and also apprises you the research being carried in that field. Thank you Prof. Shroff for such a wonderful course!
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Naseera Melethil profile image
Naseera Melethil profile image
10/10 starsCompleted
  • 1 review
  • 1 completed
6 years, 11 months ago
Thanks Dr. Gautham for being a great teacher for such an excellent course in which great concepts were taught in a simple & logical way. Really enjoyed each bit of it, lessons, quizzes, programming assignments & even the Final Exam. Really appreciate the instructors efforts for giving lights in to these deep concepts. Looking forward to the upcoming courses from Dr. Gautham, Thanks again.
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Celeste Horner profile image
Celeste Horner profile image
10/10 starsTaking Now
  • 1 review
  • 0 completed
6 years, 11 months ago
I am building an AI system. Professor Shroff's course provided exactly the knowledge I need to address the challenge of Big Data -- machine learning algorithms, map-reduce, Hadoop, etc. Thank you very much! I enjoyed the smooth and pleasant delivery of the lectures and continue to refer to the information in this course.
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Gavin Conran profile image
Gavin Conran profile image
9/10 starsCompleted
  • 25 reviews
  • 25 completed
6 years, 11 months ago
Web Intelligence includes search, logic, probability, statistics and machine learning and from a first glance can appear very confusing. More than just act as the ring that unites all these topics this course encourages you to think about the meaning of human and web intelligence.
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Ben Haley profile image
Ben Haley profile image
8/10 starsCompleted
  • 5 reviews
  • 4 completed
6 years, 11 months ago
[Edit] I upgraded this review from a 3 to a 4 star because the last set of lectures were so worthwhile. I think you can get a great deal of value from this class just by looking at the comprehensive overview in week 8 assuming you have some ml background already (e.g. you took Andrew Ng's course). Really great subject and I would love to give this class four stars except that it has had some technical snafus related to the speech rate and homework administration. If Dr. Shroff puts a little more time into this it should be a great introduction to learning from large quantities of data using modern machine learning methods.
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Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.