About this Course

203,253 recent views

Learner Career Outcomes

32%

started a new career after completing these courses

34%

got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 29 hours to complete
English

Skills you will gain

Natural Language Toolkit (NLTK)Text MiningPython ProgrammingNatural Language Processing

Learner Career Outcomes

32%

started a new career after completing these courses

34%

got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 29 hours to complete
English

Offered by

Placeholder

University of Michigan

Syllabus - What you will learn from this course

Content RatingThumbs Up92%(5,515 ratings)Info
Week
1

Week 1

9 hours to complete

Module 1: Working with Text in Python

9 hours to complete
5 videos (Total 56 min), 4 readings, 3 quizzes
5 videos
Handling Text in Python18m
Regular Expressions16m
Demonstration: Regex with Pandas and Named Groups5m
Internationalization and Issues with Non-ASCII Characters12m
4 readings
Course Syllabus10m
Help us learn more about you!!10m
Notice for Auditing Learners: Assignment Submission10m
Resources: Common issues with free text10m
2 practice exercises
Practice Quiz30m
Module 1 Quiz30m
Week
2

Week 2

7 hours to complete

Module 2: Basic Natural Language Processing

7 hours to complete
3 videos (Total 36 min)
3 videos
Basic NLP tasks with NLTK16m
Advanced NLP tasks with NLTK16m
2 practice exercises
Practice Quiz30m
Module 2 Quiz30m
Week
3

Week 3

7 hours to complete

Module 3: Classification of Text

7 hours to complete
7 videos (Total 94 min)
7 videos
Identifying Features from Text8m
Naive Bayes Classifiers19m
Naive Bayes Variations4m
Support Vector Machines24m
Learning Text Classifiers in Python15m
Demonstration: Case Study - Sentiment Analysis9m
1 practice exercise
Module 3 Quiz30m
Week
4

Week 4

6 hours to complete

Module 4: Topic Modeling

6 hours to complete
4 videos (Total 58 min), 2 readings, 3 quizzes
4 videos
Topic Modeling8m
Generative Models and LDA13m
Information Extraction18m
2 readings
Additional Resources & Readings10m
Post-Course Survey10m
2 practice exercises
Practice Quiz30m
Module 4 Quiz30m

Reviews

TOP REVIEWS FROM APPLIED TEXT MINING IN PYTHON

View all reviews

About the Applied Data Science with Python Specialization

Applied Data Science with Python

Frequently Asked Questions

More questions? Visit the Learner Help Center.