I had a lot of hope with this course but was sadly disappointed. The course content is all over the place and does not follow a structure or a flow. It talks about groupers in week 2, and talks on ETL in week 3, again brings risk stratification and some modelling concept in week 4 but linkages are missing.

My suggestion think how an analytics practitioner should follow a methodology and take him through the steps. It should start with SEMMA concept and take a practitioner through the steps like

S : what data is needed , concept and concept mapping, understand flow, input and output

E: explore : descriptive and visualizations

M: Modify: bring here concepts of grouper algorithms, risk adjustment

M : Talk here on predictive models, regressions, supervised and unsupervised learnings and risk stratification strategies

A: Talk about how you analyze output, how you train your learning set

Show with use causes scenarios of handling Fraud, Risk Adjustments and Risk Stratification.

Very good, although I would suggest the Health Informatics as a starting course

Excellent material and a great introduction to data analytics!

Very informative. Would have preferred more practical examples on data analysis

Good information. Would be nice to show actual example data demos

Thank you ...