University of Michigan

Applied Text Mining in Python

149,544 already enrolled

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Gain insight into a topic and learn the fundamentals.
4.2

(3,809 reviews)

Intermediate level
Some related experience required
Flexible schedule
Approx. 25 hours
Learn at your own pace
91%
Most learners liked this course
Gain insight into a topic and learn the fundamentals.
4.2

(3,809 reviews)

Intermediate level
Some related experience required
Flexible schedule
Approx. 25 hours
Learn at your own pace
91%
Most learners liked this course

What you'll learn

  • Understand how text is handled in Python

  • Apply basic natural language processing methods

  • Write code that groups documents by topic

  • Describe the nltk framework for manipulating text

Details to know

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Assessments

7 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the Applied Data Science with Python Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 4 modules in this course

What's included

5 videos4 readings2 assignments1 programming assignment1 discussion prompt2 ungraded labs

What's included

4 videos2 assignments1 programming assignment1 discussion prompt1 ungraded lab

What's included

7 videos1 assignment1 programming assignment1 ungraded lab

What's included

4 videos4 readings2 assignments1 programming assignment

Instructor

Instructor ratings
4.0 (279 ratings)
V. G. Vinod Vydiswaran
University of Michigan
2 Courses151,369 learners

Offered by

Recommended if you're interested in Data Analysis

Prepare for a degree

Taking this course by University of Michigan may provide you with a preview of the topics, materials and instructors in a related degree program which can help you decide if the topic or university is right for you.

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Learner reviews

Showing 3 of 3809

4.2

3,809 reviews

  • 5 stars

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    24.96%

  • 3 stars

    12.20%

  • 2 stars

    4.59%

  • 1 star

    3.51%

PP
5

Reviewed on Apr 19, 2020

CB
5

Reviewed on Sep 19, 2017

K
4

Reviewed on Nov 3, 2019

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