In this training you’ll learn:
- Exploratory Data analysis in order to achieve Data quality which involves completeness, consistency of format, cleanliness and accuracy of individual data points.
- Random sampling in order to reduce bias and yield a higher quality and representative dataset, even with big data
- The principles of experimental design that yield definitive answers to questions
- How to use regression to estimate outcomes and detect anomalies
- Key classification techniques for predicting which categories a record belongs to
- Statiscal machine learning methods that learn from data
- Unsupervised learning methods for extracting meaning from unlabel data