Components of AI Project Framework

Topics

• Scoping and data

  • Problem scoping: the 4 Ws and the problem statement
  • Data types, features, sources and training and testing data
  • System maps and Kaggle datasets

• Exploration and modelling

  • Bar graphs, histograms, line graphs, scatter plots and pie charts
  • Rule-based and learning-based approaches
  • Supervised and unsupervised learning
  • Prediction with linear regression

Learning objectives

1. Scope an AI problem and choose a suitable data representation and modelling approach.