Advanced Analytics, Forecasting, and Machine Learning Basics

Introduction

Once you can query, clean, summarise, and visualise data, you can explore methods that:

• Estimate future outcomes (forecasting)
• Predict unknown values or categories (regression, classification)
• Find hidden structure (clustering)

These methods are useful, but they require careful evaluation and clear communication of uncertainty.

This module is an introduction to analytical modelling. It does not claim that every business problem needs machine learning. Often a well-designed SQL query or simple rule is enough.

What you will learn in this module

• When forecasting is useful and how to establish a baseline
• The difference between regression, classification, and clustering
• How training and test data are used
• How to interpret common evaluation metrics
• How to recognise overfitting, leakage, and inappropriate model use