Back close

Learning Objectives

  • LO1: To define the term “Analytics” for healthcare
  • LO2: To be proficient with analytics tools for healthcare data preparation and analysis

Course Outcomes

  • CO1: Ability to understand the steps involved in the data mining process (e.g., pre-processing, classification, regression, clustering, and visualization) and apply them for analysis of healthcare data
  • CO2: Ability to describe different methods of predictive analytics and their applications in the healthcare domain
  • CO3: Ability to evaluate the data from diverse sources to create meaningful presentations

Course Contents

Getting to know your data – data pre-processing – exploring data – Probability and Uncertainty, Regression analysis – Mining patterns, associations, and correlations – classification and prediction, clustering, and outlier analysis.

The course will also include a practical component to implement theoretical concepts learnt via coding platforms such as Python and R.

Textbooks

  1. Business Analytics: Data Analysis and Decision Making by Christian Albright and Wayne Winston
  2. Data Mining Concepts and Techniques by Jiawei Han and Micheline Kamber

DISCLAIMER: The appearance of external links on this web site does not constitute endorsement by the School of Biotechnology/Amrita Vishwa Vidyapeetham or the information, products or services contained therein. For other than authorized activities, the Amrita Vishwa Vidyapeetham does not exercise any editorial control over the information you may find at these locations. These links are provided consistent with the stated purpose of this web site.

Admissions Apply Now