This course is part of the UBC Micro-certificate in Natural Language Processing to Improve Patient Care. The program consists of three courses that can be taken individually or combined into the Micro-certificate.
Natural Language Processing (NLP) is reshaping how healthcare providers interpret and use text data. This foundations course gives you a clear understanding of how NLP works, why it matters in modern healthcare and how language technologies support clinical decision-making, patient communication and operational efficiency.
Designed for healthcare professionals, analysts and researchers new to NLP, the course focuses on building practical skills for working with real-world text. You learn core concepts such as linguistic structure, text preprocessing and the evolution of language models, including large language models (LLMs). The course prepares you for more advanced analysis and healthcare-specific applications in subsequent courses.
For those who are new to NLP, we recommend starting with this course.
By the end of this course, you will be able to:
- Define NLP and describe its main areas of application
- Identify disciplines that contribute to NLP, including linguistics and computer science
- Explain the progression from early probabilistic models to modern LLMs
- Recognize real-life applications of NLP in healthcare settings
- Describe how NLP supports patients, clinicians and researchers
- Construct and interpret regular expressions for text searching and editing
- Distinguish between type I and type II errors in regex
- Explain linguistic concepts such as morphology, syntax, semantics and ambiguity
- Identify common word classes and differentiate inflectional and derivational morphology
- Describe how morphology relates to NLP tasks
- Define stemming and its role in information retrieval
- Explain the purpose of part-of-speech tagging and its relationship to ambiguity
Course activities include videos, in-course quizzes, hands-on lab assignments and discussion board participation. Optional weekly office hours offer opportunities to ask questions, review concepts and engage with peers.
Course outline
Module 1: Introduction to NLP
This module introduces the fundamentals of Natural Language Processing (NLP), with a focus on its applications in healthcare. Explore core concepts such as regular expressions, morphology and text normalization to build a foundation for understanding how language data is processed and analyzed.
Module 2: Text Preprocessing and Basic NLP Tasks
Building on foundational skills, this module dives into advanced text preprocessing techniques and basic NLP tasks. Examine sequence-to-sequence models, word structures and knowledge graphs to understand how linguistic patterns are structured and leveraged in healthcare data analysis.
Module 3: Language Models and Neural Networks
This module introduces the fundamentals of language modeling, beginning with the probabilistic representation of language at the level of letters, words and sentences.
Module 4: Large Language Models and Advanced Topics
In this module, explore the progression from traditional neural language models to advanced LLMs, including sub word embeddings, extended context windows and attention mechanisms. Understand how these features strengthen contextual analysis and text generation, and consider challenges such as bias, hallucinations and interpretability.
How am I assessed?
You are assessed through quizzes, discussion posts and hands-on lab assignments. Multiple-choice quizzes confirm your understanding of lecture content. Discussion posts evaluate your critical thinking and engagement with weekly topics, with feedback from the instructor or TAs. Lab assignments assess your ability to apply techniques and explain your results using scoring rubrics.
A minimum grade of 70% is required to pass.
Expected effort
Expect to spend five to seven hours per week to complete readings, videos, quizzes, lab assignments and optional office hours.
Technology requirements
To take this course, and for the best experience, we recommend you have access to:
- an email account
- a computer or laptop using Windows or macOS or a tablet
- the latest version of a web browser (or previous major version release)
- a Google account to access Google Drive
- a reliable internet connection
For virtual office hours, you’ll also need:
- a video camera and microphone
One day before the start of your course, we’ll email you step-by-step instructions for accessing your course.
Course format
This course is 100% online and instructor supported with weekly instructor office hours. Course work is done independently and at your own pace within deadlines set by your instructor. Log in anytime to your course to access the lessons as they become available.