Project 1: Categorization of Patients Based on the Count of Drugs for Their Therapy
Objective: This project aims to find out descriptive statistics and subset for specific clinical data problems. It will give them brief insight about Base SAS procedures and data steps.
Count the number of patients,
- Who were ever on at least one of the four drugs
- Who were ever on each of the four drugs
- Who had never been on any drug
Output should be four datasets
- TYPA – Contains the list of patients from problem 1
- TYPB – Contains the list of patients from problem 2
- TYPC – Contains the list of patients from problem 3
- SUMMARY – Contains the summary of counts for each of three problems
Project 2: Build Revenue Projections Reports
Objective: This project will give you hands-on experience in working with the SAS data analytics and business intelligence tool. You will be working on the data entered in a business enterprise setup and will aggregate, retrieve and manage that data. You will learn to create insightful reports and graphs and come up with statistical and mathematical analysis to scientifically predict the revenue projection for a particular future time frame. Upon the completion of the project, you will be well-versed in the practical aspects of data analytics, predictive modeling and data mining.
Project 3: Impact of Pre-paid Plans on the Preferences of Investors
Domain: Finance Market
Objective: The project aims to find the most impacting factors in preferences of pre-paid model; it also identifies which all are the variables highly correlated with impacting factors.
- The project aims to identify various reasons for pre-paid model preference and non-preference among the investors, to understand the penetration of the pre-paid model in the brokerage firms and, to identify the pre-paid scheme advantages and disadvantages and also to identify brand-wise market share. In addition to this, the project also looks to identify various insights that would help a newly established brand to foray deeper into the market on a large scale.
Project 4:K-Means Cluster Analysis on Iris Dataset
Objective: K-Means cluster analysis on Iris dataset to predict about the class of a flower using its petal’s dimensions
- Using the famous Iris dataset, predict the class of a flower
- Perform K-Means cluster analysis