About this Course
4.1
36 ratings
7 reviews
100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 23 hours to complete

Suggested: 5 hours/week...
Available languages

English

Subtitles: English, Spanish, Chinese (Simplified)
100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 23 hours to complete

Suggested: 5 hours/week...
Available languages

English

Subtitles: English, Spanish, Chinese (Simplified)

Syllabus - What you will learn from this course

Week
1
Hours to complete
3 hours to complete

Course Logistics and the Text Mining Tool for the Course

...
Reading
4 videos (Total 53 min), 1 reading, 1 quiz
Video4 videos
1.2 Explanations of the y-TextMiner package and the datasets9m
1.3 How-to-do: workspace installation and setup15m
1.4 How-to-use: the y-TextMiner package (download it at http://informatics.yonsei.ac.kr/yTextMiner/yTextMiner1.2.zip)13m
Reading1 reading
What is Text Mining?10m
Week
2
Hours to complete
3 hours to complete

Text Preprocessing

...
Reading
5 videos (Total 67 min), 1 reading, 1 quiz
Video5 videos
2.2 What is text mining?10m
2.3 Description of preprocessing techniques11m
2.4 How-to-do: normalization including tokenization and lemmatization20m
2.5 How-to-do: N-Grams14m
Reading1 reading
Text Preprocessing10m
Week
3
Hours to complete
3 hours to complete

Text Analysis Techniques

...
Reading
6 videos (Total 62 min), 2 readings, 1 quiz
Video6 videos
3.2 Explanations of named entity recognition11m
3.3 Explanations of dependency parsing8m
3.4 How-to-do: stopword removal and stemming14m
3.5 How-to-do: NER and POS Tagging6m
3.6 How-to-do: constituency and dependency parsing9m
Reading2 readings
Stemming and Lemmatization10m
Named Entity Recognition10m
Week
4
Hours to complete
3 hours to complete

Term Weighting and Document Classification

...
Reading
5 videos (Total 52 min), 2 readings, 1 quiz
Video5 videos
4.2 Explanations of document classification11m
4.3 Explanations of sentiment analysis9m
4.4 How-to-do: computation of tf*idf weighting10m
4.5 How-to-do: classification with Logistic Regression11m
Reading2 readings
Text Classification10m
TF-IDF10m
4.1
7 ReviewsChevron Right

Top Reviews

By KAMay 31st 2017

Excellent theory and hands-on lab codes. It'd be great if you could also cover how-to in other relevant programming languages using R or Python.

Instructor

Avatar

Min Song

Professor
Library & Information Technology

About Yonsei University

Yonsei University was established in 1885 and is the oldest private university in Korea. Yonsei’s main campus is situated minutes away from the economic, political, and cultural centers of Seoul’s metropolitan downtown. Yonsei has 3,500 eminent faculty members who are conducting cutting-edge research across all academic disciplines. There are 18 graduate schools, 22 colleges and 133 subsidiary institutions hosting a selective pool of students from around the world. Yonsei is proud of its history and reputation as a leading institution of higher education and research in Asia....

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, 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.

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