Data Science Essentials


This course gives participants the opportunity to master foundational knowledge and skills needed for data analysis, along with a discussion of common challenges and pitfalls. Participants will be introduced to various methods of data preparation, and to some intrinsic limitations of data and data analysis, and to easily avoidable pre-analysis mistakes.

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


Topic Relevance

The nature of data science is such that its skills and competencies can be brought to bear to any data problem -- the context of the problem may be different (and so can the employer), but very few data analysis techniques are only applicable in one context. The need for data analysis is common across disciplines and gaining skills in data science is applicable across all disciplines.


Learning Outcomes

  • Select appropriate methods to prepare their data for analysis
  • Anticipate challenges and limitations inherent to data and desired analysis outcomes
  • Apply data cleaning strategies to their data
  • Conduct simple analyses
  • Build simple data science pipelines to provide actionable insights



  • Participants must be comfortable with the concepts introduced in a first course in probability and statistics at the university level. Exposure to programming frameworks would be beneficial but not necessary. Participants doing a guided project must be familiar with R and/or Python.



12 hours



  • $1095 (plus tax)


Additional Information

  • Participants must be comfortable with the concepts introduced in a Probability and Statistics university-level course.
  • Participants are required to have a laptop/PC on which the current version of R/RStudio is installed (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.