Responsible Data Visualisation and Analysis (synchronous and Asynchronous E-Learning)

Skills for data analysis and communication are increasingly important in today's data-driven organisations. Yet many professionals succumb to hidden pitfalls of biased analysis, unsubstantiated interpretation and ineffective data visualisation design. This introductory course focuses on common mistakes that plague the process of exploratory data analysis and how to avoid them. It highlights how characteristics of human visual perception and psychology should guide the appropriate choice of plots and the design of data visualisations that communicates clearly and responsibly. Learners get to apply basic machine learning tools to extract inferential information from problematic data and practise designing effective data visuals based on a specific and purposeful communication objective . On completion of this course, learners will have acquired the skills to analyse data correctly and design effective visualisations to clearly communicate data-related insights at their workplace.

What You'll Learn

At the end of the course, learners will be able to:

• Design visually effective data visualisation that takes into considerations human visual perception and psychological attributes.
• Evaluate and select the appropriate plots and visualisation techniques that communicate insights embedded within the data in a clear and truthful manner.
• Conduct responsible exploratory data analysis by taking into consideration the limitations of various data analysis techniques and avoiding common data preparation and interpretation pitfalls.
• Apply basic machine learning techniques to correctly extract inferential information from the data .