Clinical Natural Language Processing (Coursera)

Clinical Natural Language Processing (Coursera)

This course teaches you the fundamentals of clinical natural language processing (NLP). In this course you will learn the basic linguistic principals underlying NLP, as well as how to write regular expressions and handle text data in R. You will also learn practical techniques for text processing to be able to extract information from clinical notes.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Finally, you will have a chance to put your skills to the test with a real-world practical application where you develop text processing algorithms to identify diabetic complications from clinical notes. You will complete this work using a free, online computational environment for data science hosted by our Industry Partner Google Cloud.

What You Will Learn

  • Recognize and distinguish the difference in complexity and sophistication of text mining, text processing, and natural language processing.
  • Write basic regular expressions to identify common clinical text.
  • Assess and select note sections that can be used to answer analytic questions.
  • Write R code to search text windows for other keywords and phrases to answer analytic questions.

Course 4 of 6 in the Clinical Data Science Specialization

Syllabus

WEEK 1
Introduction: Clinical Natural Language Processing
This module covers the basics of text mining, text processing, and natural language processing. It also provides a information on the linguistic foundations that underly NLP tools.

WEEK 2
Tools: Regular Expressions
This module introduces regular expressions, the method of text processing, and how to work with text data in R. Mastery is demonstrated through a programming assignment with applied questions.

WEEK 3
Techniques: Note Sections
This module discusses how the section of a clinical note can affect the meaning of text in the section. A programming assignment provides hands on practice with how to apply this knowledge to process clinical text.

WEEK 4
Techniques: Keyword Windows
This module discusses how you can build windows of text around keywords of interest to understand the context and meaning of how the keyword is being used. A programming assignment provides hands on practice with how to apply this technique to process clinical text.

WEEK 5
Practical Application: Identifying Patients with Diabetic Complications
Apply the tools and techniques that you have learned in the course to a real-world example!

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Advanced Tools for Digital Marketing Analytics (Coursera) Coursera
Unilever

Advanced Tools for Digital Marketing Analytics (Coursera)

The Advanced Tools for Digital Marketing Analytics course explores cutting-edge tools and technologies that are transforming the landscape of digital marketing analytics such as marketing automation and scaling strategies, predictive analytics and algorithms, video and mobile marketing trends, as well as artificial intelligence (AI), natural language processing (NLP), and ethics. You’ll also walk through preparing a portfolio and supporting a career change to digital marketing analyst.

Oct 12th 2026
4 Weeks
Introduction to Machine Learning (Coursera) Coursera
Duke University

Introduction to Machine Learning (Coursera)

This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction.

Oct 19th 2026
5-12 Weeks
Artificial Intelligence in Bioinformatics (FutureLearn) FutureLearn
Taipei Medical University

Artificial Intelligence in Bioinformatics (FutureLearn)

Discover the future of bioinformatics and learn how AI models of bioinformatics data help us to understand biological processes. Study the use of AI, machine learning, and deep learning in bioinformatics. This course will teach you the fundamentals of how AI is applied in the field of bioinformatics.

Self Paced
3 Weeks
Select Topics in Python: Natural Language Processing (Coursera) Coursera
Codio

Select Topics in Python: Natural Language Processing (Coursera)

Code and run your first NLP program in minutes without installing anything! This course is designed for learners who have some experience with Python but are a novice to NLP. The modules in this course cover processing and analyzing text; analyzing speech, syntax, and semantics; and building a chatbot.

Oct 19th 2026
3 Weeks
Natural Language Processing with Classification and Vector Spaces (Coursera) Coursera
DeepLearning.AI

Natural Language Processing with Classification and Vector Spaces (Coursera)

In Course 1 of the Natural Language Processing Specialization, offered by deeplearning.ai, you will: a) Perform sentiment analysis of tweets using logistic regression and then naïve Bayes, b) Use vector space models to discover relationships between words and use PCA to reduce the dimensionality of the vector space and visualize those relationships, and c) Write a simple English to French translation algorithm using pre-computed word embeddings and locality sensitive hashing to relate words via approximate k-nearest neighbor search.

Oct 19th 2026
4 Weeks
NLP Modelos y Algoritmos (Coursera) Coursera
Universidad Austral

NLP Modelos y Algoritmos (Coursera)

Este curso te brindará los conocimientos necesarios para la implementación de algoritmos de NLP. Mediante el uso de los últimos algoritmos más populares en NLP se procederá a dar solución a un conjunto de problemas propios del área. Para realizar este curso es necesario contar con conocimientos de programación de nivel básico a medio, deseablemente conocimiento básico del lenguaje Python y es recomendable conocer los Jupyter Notebooks en el entorno Anaconda.

Oct 26th 2026
4 Weeks
Machine Learning and NLP Basics (Coursera) Coursera
Edureka

Machine Learning and NLP Basics (Coursera)

Welcome to the "Machine Learning and NLP Basics" course, a comprehensive learning resource designed for enthusiasts keen on mastering the foundational aspects of machine learning (ML) and natural language processing (NLP). This course is structured to provide a deep dive into the core concepts, algorithms, and applications of ML and NLP, preparing you for advanced exploration and application in these fields.

Oct 12th 2026
4 Weeks
Transformer Models and BERT Model (Coursera) Coursera
Google Cloud

Transformer Models and BERT Model (Coursera)

This course introduces you to the Transformer architecture and the Bidirectional Encoder Representations from Transformers (BERT) model. You learn about the main components of the Transformer architecture, such as the self-attention mechanism, and how it is used to build the BERT model. You also learn about the different tasks that BERT can be used for, such as text classification, question answering, and natural language inference.

Oct 19th 2026
1 Week