Population Data BC

Education and training

Read more about Education and training

The Education and Training Unit (ETU) is an analysis training centre that supports research on human health, well-being and development, and responds to the training and education needs of researchers and population health professionals.

In this section of the website you will find information on:

The Professional Specialization Certificate in Population Health Data Analysis

This professional certificate provides a unique opportunity to learn a diverse set of skills from multiple disciplines.

Intro to Data Science Module 4: Advanced Unsupervised Learning (Session 2)

Read more about Intro to Data Science Module 4: Advanced Unsupervised Learning (Session 2)

This webinar is part of the Introduction to Data Science Webinar Series

Practicum session

Who uses unsupervised learning?
K-means
Expectation-maximization
Susceptibility to outliers
Dangers of labeling clusters

Watch recorded presentation below.

Intro to Data Science Module 4: Advanced Unsupervised Learning (Session 1)

Read more about Intro to Data Science Module 4: Advanced Unsupervised Learning (Session 1)

This webinar is part of the Introduction to Data Science Webinar Series

Introductory session

Who uses unsupervised learning?
K-means
Expectation-maximization
Susceptibility to outliers
Dangers of labeling clusters

Watch recorded presentation below.

Intro to Data Science Module 3: Advanced Supervised Learning (Session 2)

Read more about Intro to Data Science Module 3: Advanced Supervised Learning (Session 2)

This webinar is part of the Introduction to Data Science Webinar Series

Practicum session

Decision trees
Problems in overfit
Random Forest
Out-of-bag error vs cross-validation

Watch recorded presentation below.

Intro to Data Science Module 3: Advanced Supervised Learning (Session 1)

Read more about Intro to Data Science Module 3: Advanced Supervised Learning (Session 1)

This webinar is part of the Introduction to Data Science Webinar Series

Introductory session

Decision trees
Problems in overfit
Random Forest
Out-of-bag error vs cross-validation

Watch recorded presentation below.

Intro to Data Science Module 2: Regression and Regularization Algorithms (Session 2)

Read more about Intro to Data Science Module 2: Regression and Regularization Algorithms (Session 2)

This webinar is part of the I ntroduction to Data Science Webinar Series

Practicum session

Regression with many correlated variables
Automatic variable selection, early approaches and problems
Gradient descent
Regularization (L1 vs L2 vs ElasticNet)

Watch recorded presentation below.

Intro to Data Science Module 2: Regression and Regularization Algorithms (Session 1)

Read more about Intro to Data Science Module 2: Regression and Regularization Algorithms (Session 1)

This webinar is part of the I ntroduction to Data Science Webinar Series

Introductory session

Regression with many correlated variables
Automatic variable seletion, early approaches and problems
Gradient descent
Regularization (L1 vs L2 vs ElasticNet)

Watch recorded presentation below.

Intro to Data Science Module 1: Introduction to Machine Learning (Session 2)

Read more about Intro to Data Science Module 1: Introduction to Machine Learning (Session 2)

This webinar is part of the I ntroduction to Data Science Webinar Series

Practicum session

What is machine learning?
Supervised vs unsupervised learning
Model- and kernel-based methods
Measures of accuracy (test/train and cross-validation)
Causality and accuracy
Unsupervised learning as feature reduction

Watch recorded presentation b

Intro to Data Science Module 1: Introduction to Machine Learning (Session 1)

Read more about Intro to Data Science Module 1: Introduction to Machine Learning (Session 1)

This webinar is part of the I ntroduction to Data Science Webinar Series

Introductory session

What is machine learning?
Supervised vs unsupervised learning
Model- and kernel-based methods
Measures of accuracy (test/train and cross-validation)
Causality and accuracy
Unsupervised learning as feature reduction

Watch recorded presentatio

Introduction Data Science Webinar Series

Read more about Introduction Data Science Webinar Series

CANUE logo Presented by Population Data BC and the Canadian Urban Environmental Health Research Consortium. This FREE webinar series aims to highlight the value of specific data science methods and techniques for health and environmental research.

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