Course curriculum

  • 1

    1 - Introduction

    • 1.1 - Overview of the Course

    • 1.2 - Introducing Python

    • 1.3 - Installing Python

    • 1.4 - Installing Anaconda and Running Jupyter Notebooks

  • 2

    2 - Problem Specification

    • 2.1 - Introduction

    • 2.2 - Basic Concepts

    • 2.3 - Strings, Lists, and Range

    • 2.4 - Example: Using Python as a Calculator

    • 2.5 - Functions

    • 2.6 - Conditionals

    • 2.7 - Loops and Statements

    • 2.8 - Basic Plots

    • 2.9 - Conclusion

  • 3

    3 - Data Collection

    • 3.1 - Introduction

    • 3.2 - Arrays and Vectors

    • 3.3 - Matrices

    • 3.4 - Data Frames

    • 3.5 - Useful Functions for Data Frames

    • 3.6 - Importing External Data

    • 3.7 - Working with Datasets

    • 3.8 - Example: Natural Disaster Data

    • 3.9 - Conclusion

  • 4

    4 - Data Management

    • 4.1 - Introduction

    • 4.2 - Example: Data Management in Practice

    • 4.3 - Conclusion

  • 5

    5 - Model Building

    • 5.1 - Introduction

    • 5.2 - Object-Oriented Programming

    • 5.3 - Mathematical Functions

    • 5.4 - Statistical Functions

    • 5.5 - Statistical Models: Introduction to Linear Regression

    • 5.6 - Statistical Models: Introduction to Generalised Linear Models

    • 5.7 - Conclusion

  • 6

    6 - Visualisations and Reporting

    • 6.1 - Introduction

    • 6.2 - Visualisation Techniques

    • 6.3 - Advanced Visualisation Techniques

    • 6.4 - End-to-End Example on Reporting

    • 6.5 - Conclusion