May 04, 2019
Lectures are very good with a perfect explanation. More than lectures I liked the assignment questions. They are worth doing. You will get to know the basic foundation of text mining. :-)
Jun 26, 2018
Would love to see these courses have more practice questions in each weeks lesson. Would be helpful for repetition sake, and learning vs only doing each question once in the assignments.
By Ron B•
May 28, 2019
I am a Data Engineer with a degree in Computer Science who wanted to learn more about Natural Language Processing for a small project I wanted to build. I had no prior knowledge of NLP other than some regular expression work from college and a basic knowledge of what tokenizing, tagging and classification were at a high level. This course was a great introduction into the field and has given me a solid applicable foundation to continue my education. I wanted something that was light in theory and heavier in application and this course hit a great balance. Contrary to many of the other reviews, I didn't have a problem with the autograder, most of the time I got an answer incorrect was due to not reading the question carefully enough. The assignments were great in my opinion and actually helped drive home the points made in the lectures. I recommend this class to anyone who wants to get their feet wet in the subject.
By Aziz J•
Dec 18, 2017
This class was fantastic. It was an order of magnitude times better than the previous course, 'Applied Machine Learning,' by Kevyn Collins-Thompson. Professor V. G. Vinod Vydiswaran started most lectures with a purpose and an alluring example. He spent a good amount of time building intuition behind the algorithms and techniques involved, and saved most of the coding for challenging and satisfying homework assignments--all qualities that the previous course did not have.
Finally, professor V. G. Vinod Vydiswaran was simply energetic about teaching. I didn't have to change playrate to > 1.2x. I genuinely enjoyed his teaching style.
This course has restored my faith in the 'Applied Data Science with Python' specialization by University of Michigan and I am confident in my ability solve text classification problems in Python. Highly recommended, along with the first two courses in this specialization.
By Jingting L•
Sep 05, 2018
This is a solid intro course to NLP that covers the basics. For what it is I do think it deserves a higher rating than the 4.0 it currently has. I was worried about the amount of complaints regarding the grading machine when I started, but I was fortunate to have only experienced a very minor, inconsequential problem. Maybe I was just too traumatized by grading problems with other courses (*cough yandex big data engineering cough*) that the grading machine in this course in comparison is pretty reasonable.
For further learning, I discovered the NLP course in the Advanced Machine Learning specialization. I must say that is much more in depth and cutting-edge. Would totally recommend it as a sequel to this course.
By Vaibhav S•
Jun 26, 2018
I never knew, that the data that is present over the internet can provide such fascinating details, from which we can infer a lot. The teaching methodology of Professor Vinod where he introduces to the very basic concepts of this course, and then slowly and steadily moves to some of the core concepts of NLP is really fantastic. This course gives you all the key ingredients you need to create advanced NLP projects using python programming language.
By Yusuf E•
Apr 18, 2018
Very good overview of the NLP tasks. The assignments were again really challenging and required a lot of navigating the documentation and forums. The autograder is really frustrating sometimes though especially when it can't upload your file and you miss that part and change your correct code. Again, the assignments are really difficult without help from the forums but it was worth it.
By Maruf H•
Oct 18, 2017
Short and concise introduction to text mining and natural language processing. The presentation of the instructor is very good. The course could be organized in a better way, more course material should be added. I like the assignments so much, they taught me a lot although I think there have some problem with the Grader. Overall it's a recommended course for a CS student.
By Kedar J•
Nov 09, 2018
Great course! The assignments were at times hard to understand. Thanks to the wonderful support from the fellow students and mentors in the discussion forums, you will get most of the clarifications. Would recommend completing first 3 courses of this specialization before this one. There are a plenty of new concepts and new libraries introduced in this course.
By Yunfeng H•
Mar 27, 2019
This is a very helpful courses for text mining. It starts with cleaning data and then gradually build up the skills to classify and group texts. I love all the case studies. The assistant walks me through the tasks using the tools and methodologies mentioned in the lectures. It also helps to solve the assignments.
By Daniel N•
Sep 07, 2017
I enjoyed the course and have found the topics very interesting. One criticism is that the general quality of notebooks provided with example codes wasn't as high as for other courses in the specialization.However the lecturer was really nice and gave very good explanations even for complicated concepts.
By Γεώργιος Κ•
Apr 24, 2018
The lessons are useful, and all of the knowledge is a must have. Some things could go deeper, some needed more explanation. As a result this is a must have course for text mining but I think that the level is introductory and in real world one must have more skills to perform a respected text mining.
By Jan Z•
Sep 07, 2018
Great course overall. I have learned a lot, but last week had no tutorial example covering the topic and w4 assignment was not literally described resulting in spending a huge amount of time on trying which possible solutions will be accepted by autograder. Discussion forum helped a lot though.
By Víctor L•
Feb 14, 2018
An excellent course, it gives a full introduction to text mining, what it is useful for, covers different techniques, provides challenging activities. Maybe it lacks of a practical activity in Week 4 before the assessment, but overall the course has very good content and an excellent instructor
By Brian L•
Oct 19, 2017
Great course! I have been doing some text mining in another tool, and I learned some useful things that I was able to put to use almost immediately ... now that I have the data science part in hand, I just need to figure out some Python details in order to format my output for my client.
By Davide T•
Aug 18, 2017
Great teacher, great course. Topics are very interesting and well explained, assignments' difficult is just right. I'm sure they will put this review in some kind of sparse matrix in order to train a classifier and make previsions for future students...so it is a must-join course!
By Praveen R•
Dec 10, 2019
I learnt about NLTK package and its capabilities. It was good to know how to build vocabulary and guess missing words and match sentences lemmatizing them. Good eye opener course. There is way much more to be learnt in this subject. This is just an introduction (a good one).
By David R•
May 17, 2018
When looking at the full course in coursera, I was thinking that would be the course which would interest me the least, but at it turned out, now I'm really interested in text mining, and I'm planning to read more publication to understand that field
By Binil K•
Aug 15, 2017
This is a fantastic course though you might find some trouble with the grading part (Auto grading). This course will give you a good understanding about the various most useful techniques in text mining. Course is well structured and really helpful
By LENDRICK R•
May 12, 2019
Well-taught course, I'd been struggling with regular expressions, thank you for simplifying the concept; additionally, you've opened my eyes to an entirely new world of data science for which I can think of an immediate productive application. :-)
By BrajKishore P•
Jan 30, 2020
The overall course was well designed, all lectures were arranged in a proper sequence and all the slides and jupyter notebooks were good covering all the aspects, but I felt some difficulties in the 2nd week in POS tag, overall it was too good.
By Eunjae J•
Aug 26, 2017
This was hard but worth it. However, it didn't have extensive coding examples, which made it pretty hard to apply techniques on assignment. It might be a good way to induce creative thinking but very painstaking for students. Be aware!
By Varga I K•
Mar 05, 2019
It was a great course about data mining. It covered the basics well. I would have liked maybe another week covering the topic distribution and it would be really nice if there were a notebook for every code shown in the videos.
By Athanasios S•
May 25, 2018
I was using up to now strictly regular expressions for text mining, and that was a headache.
This course opened a new whole world to me! I strongly recommend it to any one that wants to use ML to study texts
By Валерий Н Г•
Aug 25, 2019
Great course! Even fighting with the grader didn't spoil the joy from learning new things)) Forum with useful comments of classmates is really a big deal. Thank you everyone who succeeded and shared their findings.
Oct 08, 2019
Well-structured, awesome pedagogy and challenging assignments. It has all the elements it takes to make a MOOC epic! Thanks UMich and Coursera for helping put this course together and allowing me to pursue it.
By Lucas G•
Aug 16, 2017
Good Course! The expected format for the assignment answers is often a little bit too finicky, but with careful reading of the prompts, they are all doable, and the tasks themselves are fun and useful.