Build effective machine learning models, and learn to approach and solve real-world problems across a wide array of fields. Learn to build machine learning models and evaluation criterion. Understand detailed pros and cons of one ML model (when it performs best and when it is not very efficient etc.) Learn to evaluate and validate the quality of your models based on various metrics. Finally, see the performance of the ML algorithm on a real life data.