Our Data Preparation, Feature Engineering, and Data Labelling module provides a description of the key elements relating to the topic.
- Define, identify and engineer new features
- Illustrate common feature engineering techniques and deploying feature engineering.
- Detail Data Labelling (Object detection; Time series)
- Describe Data Splits (Train, Test, & Validation; Random vs Stratified)
- Explain integration of AI into organizations and Active Learning
- Solve a worked example – Augmented AI
The delegates will learn the significance of optimizing data science output, by optimizing data preparation and utilizing feature engineering and data labelling.