{"id":3335,"date":"2019-04-09T21:23:26","date_gmt":"2019-04-09T21:23:26","guid":{"rendered":"https:\/\/canue.ca\/?p=3335"},"modified":"2019-04-09T21:23:26","modified_gmt":"2019-04-09T21:23:26","slug":"data-science-training","status":"publish","type":"post","link":"https:\/\/canue.ca\/fr\/data-science-training\/","title":{"rendered":"DATA SCIENCE TRAINING"},"content":{"rendered":"

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New to data science or looking to pick up a few new skills? Don’t miss these free webinars, guided practical tutorials and online resources featuring CANUE data.<\/strong><\/p>\n

Developed in partnership with Population Data BC<\/strong><\/p>\n

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Module 1: Introduction to Machine Learning<\/strong><\/p>\n
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  • What is machine learning?<\/li>\n
  • Supervised vs unsupervised learning<\/li>\n
  • Model- and kernel-based methods<\/li>\n
  • Measures of Accuracy (Test\/train and cross-validation)<\/li>\n
  • Causality and Accuracy<\/li>\n
  • Unsupervised learning as feature reduction<\/li>\n<\/ul>\n<\/td>\n
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Module 2: Regression and Regularization Algorithms<\/strong><\/p>\n
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  • Regression with many correlated variables<\/li>\n
  • Automatic variable selection, early approaches and problems<\/li>\n
  • Gradient descent<\/li>\n
  • Regularization\u00a0 (L1 vs L2 vs ElasticNet)<\/li>\n<\/ul>\n<\/td>\n
<\/td>\n<\/tr>\n
Module 3: Advanced Supervised Learning\u00a0<\/strong><\/p>\n
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  • Decision trees<\/li>\n
  • Problems in overfit<\/li>\n
  • Random Forest<\/li>\n
  • Out-of-bag error vs cross-validation<\/li>\n<\/ul>\n<\/td>\n
<\/td>\n<\/tr>\n
Module 4: Advanced Unsupervised Learning\u00a0<\/strong><\/p>\n
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  • Who uses unsupervised learning?<\/li>\n
  • K-means<\/li>\n
  • Expectation-maximization<\/li>\n
  • Susceptibility to outliers<\/li>\n
  • Dangers of labeling clusters<\/li>\n<\/ul>\n<\/td>\n
<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

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Dr. Aman Verma<\/strong>\u00a0 is a Data Engineer with a PhD in Epidemiology from McGill University, and an undergraduate degree in Computer Science. He has experience in developing machine learning systems with large databases, particularly for scientific data in healthcare. While he\u2019s comfortable learning any programming language, he\u2019s recently become particularly interested in R. Aman is currently involved in a number of projects, including measuring how following opioid prescription guidelines can decrease the risk of opioid overdose, modelling trajectories of chronic obstructive pulmonary disease, and assessing how to best prioritize ambulance calls using secondary healthcare data.<\/p>\n

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AN INTRODUCTION TO DATA MANAGEMENT AND CLEANING FOR ANLAYSIS IN ‘R’\u00a0\u00a0<\/strong><\/p>\n

This self paced free online course will provide you with an introduction to Data Management and Cleaning for Analysis using R Software. Each of the four modules includes a Power Point slide deck, CANUE training data, R code and associated exercises for practice.<\/p>\n

To access this resource please create a Population Data BC account here: https:\/\/my.popdata.bc.ca\/accounts\/register\/<\/a><\/p>\n

Once your account has been approved you will be able to access the Education and Training site and self enroll in this and other free online courses.<\/p>\n

Topics covered include:<\/p>\n