3. About the Course
This course will cover the major techniques for mining and analyzing text data to discover
interesting patterns, extract useful knowledge, and support decision making, with an emphasis on
statistical approaches that can be generally applied to arbitrary text data in any natural language with
no or minimum human effort.
Detailed analysis of text data requires understanding of natural language text, which is known to be
a difficult task for computers. However, a number of statistical approaches have been shown to work
well for the "shallow" but robust analysis of text data for pattern finding and knowledge discovery.
You will learn the basic concepts, principles, and major algorithms in text mining and their
potential applications.
Course Syllabus
This course will be covering the following topics:
Overview of text mining and analytics
Natural language processing and text representation
Word association mining
Topic mining and analysis with statistical topic models
Text clustering and categorization
Opinion mining and sentiment analysis
Integrative analysis of text and structured data
Recommended Background
Proficiency in programming, especially with C++. Basic knowledge of probability and statistics.
Course Format
The course will have video lectures, accompanied by quizzes and peer graded assignments.
FAQ
How does this course fit into the Data Mining Specialization?
This is the fourth course in the track.
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