About this Course

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Shareable Certificate
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Intermediate Level
Approx. 26 hours to complete
English
Subtitles: English, Korean

What you will 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

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. 26 hours to complete
English
Subtitles: English, Korean

Offered by

University of Michigan logo

University of Michigan

Syllabus - What you will learn from this course

Content RatingThumbs Up92%(4,968 ratings)Info
Week
1

Week 1

8 hours to complete

Module 1: Working with Text in Python

8 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 Quiz8m
Module 1 Quiz12m
Week
2

Week 2

6 hours to complete

Module 2: Basic Natural Language Processing

6 hours to complete
3 videos (Total 36 min)
3 videos
Basic NLP tasks with NLTK16m
Advanced NLP tasks with NLTK16m
2 practice exercises
Practice Quiz4m
Module 2 Quiz10m
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 Quiz14m
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 Quiz4m
Module 4 Quiz10m

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About the Applied Data Science with Python Specialization

The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data. Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate....
Applied Data Science with Python

Frequently Asked Questions

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

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    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

  • This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.

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