Certificate Program

Introduction to Data Analytics in Healthcare (IDAH)

Key Information

  • PROGRAM OFFERING DATE: 23 January, 2027

  • DURATION AND MODE:  Total 16 weeks; Virtual Lectures: 8 weeks
    Experiential Learning: 8 weeks (available in both virtual/in-person)

  • PROGRAM FEE: ₹8,000

  • TIME COMMITMENT: 1 hour per week lecture + self-paced Learning

Program Overview

In recent years, the volume of health data generated and collected has surged dramatically. This wealth of data holds significant potential to enhance healthcare delivery, improve health outcomes, and advance research. However, it also presents a substantial challenge: how can we efficiently extract meaningful and actionable insights from such vast and diverse datasets?

In recent years, the volume of health data generated and collected has surged dramatically. This wealth of data holds significant potential to enhance healthcare delivery, improve health outcomes, and advance research. However, it also presents a substantial challenge: how can we efficiently extract meaningful and actionable insights from such vast and diverse datasets?

Data analytics involves examining datasets to uncover patterns, trends, and other valuable insights that inform healthcare decision-making at both individual and population levels. Leveraging data analytics in healthcare has opened unprecedented opportunities to address and combat contemporary challenges in public health. Effective transformation of raw data into actionable insights can play a pivotal role in ensuring that complex health data is accurately interpreted and is utilised to improve healthcare delivery and public health outcomes.

Introduction to Data Analytics in Healthcare (IDAH) empowers students to acquire skills in the analysis of data to look for trends and patterns that can help to improve health outcomes by supporting evidence-based decision making. IDAH can equip individuals to grasp the potential of big data to handle vast and voluminous datasets and extract insights to provide better healthcare and drive advancements. The program will build familiarity with Artificial Intelligence (AI) and Machine Learning (ML) and their role in driving the shift towards precision and value-based healthcare. In addition to this, IDAH will help learners to understand the dynamics of social media in healthcare data analytics to enable a clear and concise communication of public health data into meaningful information for broader stakeholders to navigate the complexities of modern data-driven environments. This can eventually make our healthcare system more responsive, informed, and will help to maintain the alignment with real-world experiences. Furthermore, students can collaborate across disciplines, working effectively with interdisciplinary teams to address health-related challenges by integrating knowledge from healthcare, analytics, information technology, and communication.

The core objective of the program is to develop a comprehensive understanding of harnessing data analytics in healthcare. This enables learners to proficiently analyse datasets, extract actionable insights, and convey findings clearly to address contemporary health-related challenges.

Based on the principles of Bloom’s Taxonomy, learning outcomes of the program include:

  1. Identify key concepts and terminology related to healthcare analytics, data science, exploratory data analysis, warehousing, and machine learning.
  2. Comprehend the role of data analytics in the evidence-based decision-making process while designing and implementing any public health program.
  3. Acquaint oneself with different types and applications of big data in real-time surveillance for healthcare, enabling evidence-based decision-making for effective public health interventions.
  4. Understand the role of ethics and the legal framework in maintaining regulatory standards while leveraging analytics in healthcare.
  5. Critically examine datasets to identify underlying patterns and trends, facilitating evidence-based decisions using R, data analysis software.
  6. Create data-driven public health solutions by applying healthcare data analytics and big data methodologies to address population health challenges and inform strategic decision-making.

The program is delivered virtually which spans 4 months. It includes 2 months of virtual training and 2 months of experiential learning (virtual/in-person). The entire program includes 8 topics. Each topic is delivered weekly in the form of weekly lectures, case studies, hands-on exercises, and reading material. Assessments are conducted both during and after the module completion. Students also participate in various community outreach activities.

  • COPHI (Community of Population Health Informatics): Fortnightly interaction on our discussion forum
  • Monthly research seminar series
  • Opportunity to participate in community outreach initiatives, implementing public health/digital interventions
  • Participation in our v-INSPIRE Experiential learning program that aims to enhance academic and non-academic skills of students by providing an innovative and participatory learning experience
  • Participation in our Career and Mentorship Program (CAMP) that aims to provide students an opportunity to explore career pathways in the field of public health. 
  • Opportunity to engage in hackathon/ and other innovative initiatives
  • Opportunity to participate in national and international conferences

This is a flexible, self-paced hybrid program (including both Asynchronous and synchronous learning), with interactive teaching, through a series of weekly lectures, case studies, reading material, and discussions. In addition, the program will utilize problem-based learning approaches to assess student skills, knowledge, and competencies. Additionally, the program offers a platform for students to voice their opinions on the Discussion Forum and periodic seminars, along with hands-on research experience.

 

Module Topics Teaching and Activity
1 Basics of Healthcare Analytics Lecture, Reading and Class Discussion
2 Harnessing Big Data-Driven Healthcare Lecture, Reading and Class Discussion
3 Healthcare Data Warehousing Lecture, Reading and Class Discussion
4 Overview of Exploratory Data Analysis (EDA) Lecture, Reading and Class Discussion
5 R for Health Data Analysis Lecture, Reading and Class Discussion
6 Artificial Intelligence and Machine Learning in Healthcare Lecture, Reading and Class Discussion
7 Leveraging Social Media and Analytics Lecture, Reading and Class Discussion
8 Understanding Ethics and Healthcare Analytics Regulation Lecture, Reading and Class Discussion
8-week experiential learning program featuring research seminars/case study–based learning.

 

  • Opportunity to present research findings at national and international conferences
  • Opportunity to build their portfolio for furthering their career across multiple healthcare pathways
  • Guidance and Mentorship to publish their research work in peer-reviewed scientific journals.
  • A certificate will be provided upon participation in the Experiential Learning, in addition to successful completion of the certificate program.