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Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
The ‘Clinical Natural Language Processing’ online course is focused on delivering students insights on the strategies and tools involved in the processing of texts and collecting information from clinical data. This data analysis course is part of the clinical data science specialization and is provided by Coursera in association with the University of Colorado. The students of this course can explore the text data in R and can gain knowledge of the practical applications of finding out any diabetic issues from the clinical data.
The course can be completed within an estimated period of twelve hours in about three weeks and the students can study at their own pace. The instructor for this intermediate-level program is Laura K. Wiley, an Assistant Professor from the Division of Biomedical Informatics and Personalized Medicine at the Anschutz Medical Campus.
The ‘Clinical Natural Language Processing’ online training program ensures students with an industrially significant course certificate that can be shared online for the development of their career.
The Highlights
- Online mode
- 12 hours course
- Free registration
- Self-paced learning
- Course certificate
- Subtitles
- Flexible deadlines
- Intermediate level training
Programme Offerings
- Online Classes
- video lectures
- Readings
- quizzes
- Practice Exercises
- Self-study
- Audit mode
- Certificate.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Coursera |
The fees for the course Clinical Natural Language Processing is -
| Head | Amount in INR |
| 1 month | Rs. 4,117 |
| 3 month | Rs. 8,234 |
| 6 month | Rs. 12,352 |
Eligibility Criteria
Certificate qualifying details
The students who are part of the ‘Clinical Natural Language Processing’ certification by Coursera are required to get their course completion certificate after finishing the course, graded assessments, and tests.
What you will learn
The ‘Clinical Natural Language Processing’ certification syllabus is developed for the students to enhance their knowledge and get familiar with the following aspects,
- Identification of the significance of data analysis concepts of text processing, text mining, and natural language processing.
- Evaluate and determine note sections to identify answers for analytical questions.
- Draft basic and fundamental expressions to know the common clinical data.
- R code writing to find text windows for keywords and phrases to answer questions that are analytical.
Who it is for
The ‘Clinical Natural Language Processing’ online certification program is directed at the students and industry professionals who wish to learn about the techniques of NLP in the clinical context and for processing clinical data.
Admission Details
The admission process for the ‘Clinical Natural Language Processing’ online course is done online through the Coursera website.
Step 1: Go to the course page using the link-https://www.coursera.org/learn/clinical-natural-language-processing
Step 2: Find the ‘Enroll For Free’ link
Step 3: Enter the relevant information on the registration form.
Step 4: Make the payment and join the course.
Application Details
The ‘Clinical Natural Language Processing’ training requires students to fill in their name, email address, and password for the course account. The students can also join the course using their Google, Facebook, and Apple IDs.
The Syllabus
Videos
- Welcome to Clinical Natural Language Processing
- Introduction to Clinical Natural Language Processing
- NLP Fundamentals: Linguistics
- NLP Fundamentals: Morphology & Lexicography
- NLP Fundamentals: Syntax
- NLP Fundamentals: Semantics & Pragmatics
- NLP Fundamentals: Wrap Up
Readings
- Introduction to Specialization Instructors
- Course Policies
- Accessing Course Data and Technology Platform
Practice exercise
- Week 1 Assessment
Videos
- Introduction to Regular Expressions
- Text Processing in the Tidyverse
- Tips and Tricks for Text Processing
Readings
- Regular Expressions and Text Processing in R1h
- Note about the Assessment
Practice exercises
- Regular Expressions and Text Processing in R - Try it Out For Yourself Exercises
- Week 2 Assessment
Videos
- Techniques: Note Sections
- Clinical Note Types: History and Physical Notes
- Clinical Note Types: Discharge Summaries
- Clinical Note Types: Radiology Reports
Readings
- Note Section Techniques
- Note about the Assessment
Practice exercises
- Note Section Techniques - Try It Out For Yourself Exercises
- Week 3 Assessment
Video
- Techniques: Keyword Windows
Readings
- Keyword Windows Techniques
- Note about the Assessment
Practice exercises
- Keyword Windows Techniques - Try it Out For Yourself Answers
- Week 4 Assessment
Video
- Welcome to Practical Applications!
Instructors
CU Boulder Frequently Asked Questions (FAQ's)
It takes about twelve hours to complete the program.
There are no prerequisites for this course.
The course is provided by Coursera.
Yes, you are given subtitles in English.
Yes, you can use the EMI options available.