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Course Description

Clinical notes and patient records contain vast amounts of data, but this data is not always in a format machines can interpret. In this course, you will discover how natural language processing (NLP) can help you transform free text into structured data for extracting insights. You’ll start by reviewing NLP methods to prepare raw text for machine analysis. Using the Python package spaCy, you’ll perform NLP tasks like sentence splitting, tokenization, part-of-speech tagging, and parsing.

You will then explore key NLP applications. Using the scikit-learn and scispaCy Python packages, you’ll apply text classification and named entity recognition (NER) to gain insights from medical texts. Finally, you’ll advance to deep learning models, examining their application for healthcare tasks such as the de-identification of patient data. You will also consider the ethical implications of using such models, focusing on patient security and privacy. By the end of this course, you’ll gain hands-on experience using NLP techniques to extract insights from healthcare data while also considering how to apply these methods ethically and responsibly.

Students must have intermediate proficiency in Python programming and machine learning to succeed in this course.

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

  • Machine Learning in Healthcare
  • Data Management in Healthcare

Faculty Author

Yifan Peng

Benefits to the Learner

  • Examine classical natural language processing methods, including sentence splitting, tokenization, part-of-speech tagging, and dependency parsing
  • Examine NLP applications, including text classification and sequential labeling within the healthcare sector
  • Explore BERT and generative AI as well as their applications within the healthcare sector

Target Audience

  • Data scientists
  • Medical and health services managers
  • Database and IT data architects
  • Data engineers
  • Digital transformation managers
  • Clinicians with experience in informatics
  • Biomedical and clinical informatics fellows
  • Aspiring medical database managers or administrators

Applies Towards the Following Certificates

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Type
2 week
Dates
Apr 09, 2025 to Apr 22, 2025
Total Number of Hours
14.0
Course Fee(s)
Regular Price $999.00
Type
2 week
Dates
May 28, 2025 to Jun 10, 2025
Total Number of Hours
14.0
Course Fee(s)
Regular Price $999.00
Type
2 week
Dates
Jul 02, 2025 to Jul 15, 2025
Total Number of Hours
14.0
Course Fee(s)
Regular Price $999.00
Type
2 week
Dates
Aug 20, 2025 to Sep 02, 2025
Total Number of Hours
14.0
Course Fee(s)
Regular Price $999.00
Type
2 week
Dates
Sep 24, 2025 to Oct 07, 2025
Total Number of Hours
14.0
Course Fee(s)
Regular Price $999.00
Type
2 week
Dates
Nov 12, 2025 to Nov 25, 2025
Total Number of Hours
14.0
Course Fee(s)
Regular Price $999.00
Type
2 week
Dates
Dec 17, 2025 to Dec 30, 2025
Total Number of Hours
14.0
Course Fee(s)
Regular Price $999.00
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