Introduction to Machine Learning

Overview

This course leads the participants to analyze and discuss the general tasks and problems of statistical learning (machine learning), as well as their pitfalls. In this course, participants will be introduced to simple association rules, mining, classification, and clustering algorithms.

Following the course, the participants have the option of working on a guided project, getting feedback from the instructor.

 

Topic Relevance

The need for basic skills in machine learning is common across disciplines and an integral part of data sciences competencies. These basic skills will be of use to developing data scientists across all disciplines.

 

Learning Outcomes

  • Differentiate between situations which require a supervised learning approach and those which require an unsupervised approach (or some combination of both)
  • Identify strategies used to overcome common real-world statistical learning issues and challenges
  • Recognize the variety of machine learning algorithms available to them
  • Implement simple machine learning algorithms to provide actionable insights
  • Build a simple data analysis pipeline incorporating machine learning components

 

Audience

  • Familiarity with the concepts introduced in the courses Data Science Essentials (data preparation, data cleaning), and Data Visualization and Dashboards (data exploration) are required. Familiarity with optimization methods would be beneficial but not required. Participants doing a guided project must be familiar with R, the tidyverse, and/or Python.

 

Duration

12 hours

 

Cost

  • $1095 (plus tax)

 

Additional Information

  • Participants are required to have a laptop/PC on which the current version of R/RStudio is installed (and for which they may require administrative authorisation to install packages).

 

Featured Instructors

Dr. Boily is a professor in the Mathematics Department and has offered upwards of 200+ training days in data science, analysis, visualization, and machine learning to 60+ cohorts of professionals in the Ottawa region since 2015.

 

Sessions