Health Data Analysis and Machine Learning

This course is part of the UBC Micro-certificate in Health Data Analytics: Opportunities and Applications program. The program consists of three courses that can be taken individually or combined into the Micro-certificate.

Health Data Analysis and Machine Learning will help you gain proficiency in using WEKA for data handling, analysis, visualization, and executing machine learning processes. The course covers visualizing datasets and data reduction, and introduces foundational concepts including principal component analysis and data clustering. You will become familiar with essential machine learning terms, practice basic algorithms, and gain introductory knowledge of Natural Language Processing (NLP) and feature extraction techniques.

By the end of the course, you will be able to:

• master the usage of WEKA for data preprocessing, analysis, visualization and implementation of machine learning algorithms
• provide multiple views, deal with complexity and describe the pros and cons of various ways to perform data reduction
• introduce principal component analysis and data clustering
• learn basic machine learning terminology
• perform simple machine learning algorithms
• develop a basic understanding of NLP and feature extraction techniques.

Course activities include readings, videos, tutorials, virtual small group discussions and online discussion boards.

How am I assessed?

Assessment takes place on successful completion of short assignments, student reflections and quizzes each week. These activities are marked using a proficiency scale, and your instructor provides you with informal feedback. The minimum passing grade for this course is 70%.

Expected effort

The duration of each course is four weeks, and the approximate time commitment expected for completing the course is 25 hours. Participants are expected to allocate approximately six hours per week to engage with the course materials, which encompass lecture videos, readings and activities.

Technology requirements

To take this course, and for the best experience, we recommend you have access to:

• an email account
• a computer, laptop or tablet
• the latest version of a web browser (or previous major version release)
• a reliable internet connection
• a video camera and microphone

We will be using WEKA (Waikato Environment for Knowledge Analysis), which is a data analysis software requiring following specifications:

• a modern computer, preferably not more than 4-5 years old with:
  • a dual-core processor
  • a minimum of 4GB RAM (8GB recommended)
  • a minimum of 2GB free disk space
• Operating system: Windows, macOS, or Linux

Software development platform: Java 8 or higher must be installed.

Course format

This course is 100% online instructor supported with weekly office hours.

Each week there will be an opportunity to attend instructor or teaching assistant office hours if you need any help with course content. There will also be weekly small group discussions with your peers to provide you with a community of practice and enable you to network with others working in this field in BC.

The weekly live, virtual office hours are Thursdays, 6 to 7pm Pacific Times (subject to change).