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Course Description

We have all been misunderstood when sending a text message or email, as tone often does not translate well in written communication. Similarly, computers can have a hard time discerning the meaning of words if they are being used sarcastically, such as when we say “Great weather” when it’s raining. If you are automatically processing reviews of your product, a negative review will have many of the same key words as a positive one, so you will need to be able to train a model to distinguish between a good review and a bad review. This is where semantic and sentiment analysis come in.

In this course, you will examine many kinds of semantic relationships that words can have (such as hypernyms, hyponyms, or meronyms), which go a long way toward extracting the meaning of documents at scale. You will also implement named entity recognition to identify proper nouns within a document and use several techniques to determine the sentiment of text: Is the tone positive or negative? These invaluable skills can easily turn the tide in a difficult project for your team at work or on the path toward achieving your personal goals.

You are required to have completed the following courses or have equivalent experience before taking this course:

  • Natural Language Processing Fundamentals
  • Transforming Text Into Numeric Vectors
  • Classifying Documents With Supervised Machine Learning
  • Topic Modeling With Unsupervised Machine Learning
  • Clustering Documents With Unsupervised Machine Learning

Faculty Author

Dr. Oleg Melnikov

Benefits to the Learner

  • Extract meaning from a document using semantic analysis
  • Locate proper nouns within a document using named entity recognition
  • Determine the positive or negative sentiment of documents using several analytical techniques

Target Audience

  • Engineers
  • Software developers
  • Computer scientists new to NLP
  • Data scientists
  • Analysts
  • Researchers
  • Linguists

Applies Towards the Following Certificates

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Enroll Now - Select a section to enroll in
Type
3 week
Dates
May 15, 2024 to Jun 04, 2024
Total Number of Hours
24.0
Course Fee(s)
Regular Price $1,199.00
Type
3 week
Dates
Jul 24, 2024 to Aug 13, 2024
Total Number of Hours
24.0
Course Fee(s)
Regular Price $1,199.00
Type
3 week
Dates
Oct 02, 2024 to Oct 22, 2024
Total Number of Hours
24.0
Course Fee(s)
Regular Price $1,199.00
Type
3 week
Dates
Dec 11, 2024 to Dec 31, 2024
Total Number of Hours
24.0
Course Fee(s)
Regular Price $1,199.00
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