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學生對 密歇根大学 提供的 Applied Text Mining in Python 的評價和反饋

3,455 個評分
662 條評論


This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling). This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python....



Quite challenging but also quite a sense of accomplishment when you finish the course. I learned a lot and think this was the course I preferred of the entire specialization. I highly recommend it!


Excellent course to get started with text mining and NLP with Python. The course goes over the most essential elements involved with dealing with free text. Definitely worth the time I spent on it.


626 - Applied Text Mining in Python 的 650 個評論(共 653 個)

創建者 Guo X W


This is my least favourite course in the specialisation. Natural language processing is an exciting field and I think there is a lot more potential to enthuse and engage students. The instructor scratches the surface of text mining by going through brief sets of codes on ppt slides. I thought it would be meaningful to use more real-world datasets (as in the previous courses in the specialisation) and have students follow through some examples on Jupyter Notebook. I also felt that the exposition by the instructor was not the most intuitive or lucid. It could be much clearer.

創建者 Matt P


This course was much less helpful than others in the Specialization. The assignments are poorly conceived, and submissions are beset by finicky autograder issues. Certainly, data cleaning and code debugging are critical skills for text mining, but I find it difficult to believe that "try to understand what output a function should submit so as to satisfy the current autograder" is a useful way to teach text mining.

I hope this course will be re-done to bring it in line with the quality of the others in the Specialization.

創建者 Denys P


The course is a joke. Its outdated and not supported, you literally need to spend hours to try and figure and emulate versions used by autograder and even the file structure for files used by default is not accurate and you get file read errors on predefined by them functions on their own virtual environment and need to fix these for them!!! The virtual machine env provided is super slow so need to use your own. Very bad user experience and horrible use of time!

創建者 Dr. D W


What a horrible course. Especially the assignments are such an unbelievable waste of time. Instead of focusing on important concepts and applications, one has to spend hours one "pleasing the autograder" by renaming columns and reading the discussion pages for the correct interpretation of all the ambiguously formulated questions. Very sad! Would be good for everyone if this was removed from the (otherwise great) series "Applied Data Science in Python".

創建者 Maximilian W


Serious sub-par course in the specialisation. The lecturer is good, but sadly the assignments are terrible. Thus the reinforcement - and reliability to problem solving - of the content is poor.

Given the high standard of the first three modules in this specialisation, this is really a shame. I would urge learners to consider whether there is much point in doing this course (other than to get the specialisation completed).

創建者 Eduardo C F


I was under the impression that the course is incomplete, especially week 4, which has no notebook examples of the theory presented. I needed to look at other sites for basic information. I could only complete the exercises because they are easy, otherwise, with the code presented during the course, I would not have been able to. I suggest strengthening the example code in python (see week 3, good code)

創建者 Ruben G C


I have to say that the previous three courses were very well explained, with good examples and python code. However, this course is not well explained nor documented. It is a pity that the quality of the whole specialization program gets considerably reduced due to this course. The assignments do not allow you to learn and you may not pass them due to small differences in the coding.

創建者 Justin M


Videos are so high-level that they don't help at all understanding the necessary code. Assignments have spelling errors and ambiguity. Week 4 is missing the sample code notebook. I eventually found the sample code notebook in the forums, but this was a big cause of frustrations as I had zero context for how to do the assignment.

創建者 Daniel B


I don't feel like I learned anything even though I passed with 100%. This course desperately needs more insightful quizzes and assignments, and the lectures should actually explain how to do "applied text mining" rather than just glossing over some terminology.

創建者 Nicholas P


Unless the instructional staff updates the programming assignments to reflect updates in packages and ensures they can run without additions, do not take this course. It is a terrible reflection on the University of Michigan.

創建者 Didier C


The subject is interesting however the lectures are too shallow and the assignments too difficult. You should be expected to do more study after the lecture for sure but for this course, it was a lot.

創建者 Venkata S M B


Not a great course. I'd skip it. The assignments were just trying out different parameters. Nothing related to machine learning/using Python was discussed in the class (may be 2%). Didn't lean much.



Video lectures are just been run through. No clear explanation at all. On the top of that, assignments are freaking difficult being totally irrelevant to the material taught in the video lectures.

創建者 Mark R


Interesting topic, but a really poor course with barely any content.

Around an hour or less of lectures a week.

I've taken a lot of MOOC's on Coursera and other platforms and this one is poor

創建者 Luis d l O


Too simple. Few information and content, and extremely simple (though with a lot of problems) assignments.

創建者 Dario M


The difficulty of the assignments is in no way related to the simpleness of the lectures.

創建者 Akshat S


The NLTK library was not explained properly. No code explanation was provided.

創建者 Zhongtian Y


Teacher does not explain well and lectures are not detailed.

創建者 PS


Horrible assignment and horribl week 3 and 4. Please avoid!

創建者 Jose Á P L


Este curso no vale para nada, por favor no lo hagais!!!

創建者 Vivek G


Only useful for coarse understanding of the topic.

創建者 kumar s


tired of auto grader,...and prof not interested

創建者 Feng Q


totally can't understand the Indian accent.

創建者 Mahmoud


the worst ever I took here in Coursera

創建者 Sandy F


worst course in the series by far.