What is this course about?

This module will give you basic skills in data analytics. Good data analytics is not just about collecting data, it’s about understanding data, whether big or small, and using data in a smart way, to try to drive insight. The topic areas covered in this course are:

1. Presenting and summarising your data

2. Decision-making under uncertainty

3. Data-based decision-making

4. Modelling for decision-making

This module has been developed by the Imperial College Business School. As such, it is focused on applications within real-world scenarios, usually within the corporate world. However, these practical data analytics skills are highly transferable and useful to any student of Science and Engineering.

What are the learning outcomes?

In the presenting and summarising data section, you will learn:

  • to encode data
  • what kind of data we encounter in real-life
  • how to present that data and how to visualise the data effectively
  • to use summary statistics

In the decision-making under uncertainty section, you will learn:

  • to compute probabilities
  • how to use probability trees and decision trees in order to make your decision
  • to apply sensitivity analysis in order to make decisions under uncertainty

In the data-based decision-making section, you will learn:

  • about the use of samples and why we need them
  • how to determine how big our samples should be in order to achieve certain objectives
  • how to extrapolate from samples to the whole population

In the modelling for decision-making section, you will learn

  • the concept of correlation analysis
  • how models and data can be used in order to help us make decisions
  • how models are used for optimisation, forecasting and scenario planning

Who is this course aimed at?

This module is built by Imperial College Business School, but data analytics is a topic relevant to all STEM degrees. 

How will this course be delivered?

This is an asynchronous module and will be delivered online, via the EdX Edge platform. Instructions on how to access the course can be found in the links to courses tab of your Microsoft Teams space.

How much time will the course take up?

A total of approximately 23 hours to be distributed in time according to your own preference.