Complete Data Wrangling & Data Visualisation With Python

Complete Data Wrangling & Data Visualisation With Python


I have several years of experience in analyzing real life data from different sources using statistical modeling and producing publications for international peer reviewed journals. If you find statistics books & manuals too vague, expensive & not practical, then you’re going to love this course!

I created this course to take you by hand and teach you all the concepts, and tackle the most fundamental building block on practical data science- data wrangling and visualisation.


This course is your sure-fire way of acquiring the knowledge and statistical data analysis wrangling and visualisation skills that I acquired from the rigorous training I received at 2 of the best universities in the world, perusal of numerous books and publishing statistically rich papers in renowned international journal like PLOS One.

To be more specific, here’s what the course will do for you:  (a) It will take you (even if you have no prior statistical modelling/analysis background) from a basic level to performing some of the most common data wrangling tasks in Python.  (b) It will equip you to use some of the most important Python data wrangling and visualisation packages such as seaborn.  (c) It will Introduce some of the most important data visualisation concepts to you in a practical manner such that you can apply these concepts for practical data analysis and interpretation.

(d) You will also be able to decide which wrangling and visualisation techniques are best suited to answer your research questions and applicable to your data and interpret the results.

The course will mostly focus on helping you implement different techniques on real-life data such as Olympic and Nobel Prize winners

After each video you will learn a new concept or technique which you may apply to your own projects immediately! Reinforce your knowledge through practical quizzes and assignments.

Who this course is for:

  • Students Interested In Getting Started With Data Science Applications In The Jupyter Environment
  • Students Interested in Learning About the Common Pre-processing Data Tasks
  • Students Interested in Gaining Exposure to Common Python Packages Such As pandas
  • Those Interested in Learning About Different Kinds of Data Visualisations
  • Those Interested in Learning to Create Publication Quality Visualisations


  • The Ability To Install the Anaconda Environment On Your Computer/Laptop
  • Know how to install and load packages in Anaconda
  • Interest in Learning to Process and Visualise Real Data

Last updated 4/2019


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