About this Course

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Intermediate Level
Approx. 13 hours to complete
English
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. 13 hours to complete
English

Offered by

Placeholder

Yonsei University

Syllabus - What you will learn from this course

Week
1

Week 1

2 hours to complete

Course Logistics and the Text Mining Tool for the Course

2 hours to complete
4 videos (Total 53 min), 1 reading, 1 quiz
4 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
1 reading
What is Text Mining?10m
Week
2

Week 2

2 hours to complete

Text Preprocessing

2 hours to complete
5 videos (Total 67 min), 1 reading, 1 quiz
5 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
1 reading
Text Preprocessing10m
Week
3

Week 3

2 hours to complete

Text Analysis Techniques

2 hours to complete
6 videos (Total 62 min), 2 readings, 1 quiz
6 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
2 readings
Stemming and Lemmatization10m
Named Entity Recognition10m
Week
4

Week 4

2 hours to complete

Term Weighting and Document Classification

2 hours to complete
5 videos (Total 52 min), 2 readings, 1 quiz
5 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
2 readings
Text Classification10m
TF-IDF10m

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