This program provides a strong foundation in data analytics by bringing a diverse body of knowledge starting from exploratory data analysis (EDA), applied statistics, applied mathematics, computer science, optimisation, consumer behaviour and decision theory.
Learning Outcomes. By the end of this course you will be able to:
- Given a problem statement or use case, one will be able to identify what all data sets would be required for the analysis
- Do the EDA (Exploratory Data Analysis) on the data sets and identify what all Machine Learning techniques or Models to be tried out
- Validate the accuracy of the models with the test or hold-out data set
- Finalize one best model or ensemble multiple models.