Exploratory Data Analysis 

Write your awesome label here.
Empty space, drag to resize

How you should study for this module?

  • View all video lessons and corresponding slide sets
  • Practice with the code samples from the lessons
  • Complete all topics assignments. (Mandatory) 
  • Undertake the case study
  • Study the exam practice questions before the exam
Recommended reading lists
Applied Unsupervised Learning with R, Alok Malik and Bradford Tuckfield, 1st Edition. (Packt Publishing, 2019). 322 pages.
Module overview
Most industry analysis starts with exploratory data analysis and a thorough study of this will help you to perform data health checks and provide initial business insights. You will gain a sound understanding of R and Python programming, as well as the fundamentals of statistics. This includes writing R and Python commands for data management, basic statistical analysis, performing descriptive statistics and presenting data using appropriate graphs and diagrams. This unit serves as a foundation for advanced analytics.
Empty space, drag to resize
assessment requirments
In order to complete this module successfully you will need to 
  1. Attend the scheduled live classes (or view the recorded session)
  2. Watch all learning content on the platform
  3. Complete all topic assignments
  4. Submit case study answers
  5. Pass the module exam with a minimum grade of 50%

Empty space, drag to resize
EDA Certificate of Completion

Course Lessons

Created with