To support our site, Class Central may be compensated by some course providers.

Applied Text Mining in Python

University of Michigan via Coursera

students interested
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.

Taught by

Christopher Brooks, Kevyn Collins-Thompson, Daniel Romero and V. G. Vinod Vydiswaran
Cost Free Online Course (Audit)
Pace Upcoming
Subject Data Science
Provider Coursera
Language English
Certificates Paid Certificate Available
Calendar 4 weeks long
Sign up for free? Learn how
+ Add to My Courses
FAQ View All
What are MOOCs?
MOOCs stand for Massive Open Online Courses. These are free online courses from universities around the world (eg. Stanford Harvard MIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you.  They also have student discussion forums, homework/assignments, and online quizzes or exams.

Review for Coursera's Applied Text Mining in Python
1.0 Based on 1 reviews

  • 5 star 0%
  • 4 star 0%
  • 3 star 0%
  • 2 star 0%
  • 1 star 100%

Did you take this course? Share your experience with other students.

Write a review
  • 1
1.0 7 months ago
by Will Wheeler is taking this course right now.
This class is rife with errors. The main problem is the very finicky autograder, which is frequently programmed incorrectly and often gives no useful feedback.

Other problems include readings in the first week that rely on modules from later weeks, incomplete instructions (e.g., how to break ties in a sorted list), and use of Python 2.7 in examples (although the class is in Python 3.5).

At the beginning of the course (but not in the advertised materials), they emphasize "self-learning," which really means going to the discussion forums and using Google to look up errors.

Because of the problems with the autograder and the emphasis on self-learning, estimated completion times are wildly inaccurate. The first week's assignment is beyond ridiculous, and people on the discussion forums report taking 20 or as much as 43 hours for a stated three-hour assignment!
Was this review helpful to you? Yes
  • 1

Class Central

Get personalized course recommendations, track subjects and courses with reminders, and more.