Inspiration to start the course and its alignment with larger goals of the university
The Indraprastha Institute of Information Technology (IIIT-Delhi), a premier IT university in Delhi with departments and interdisciplinary centers with expertise in healthcare, AI, social sciences, humanities, conceived the Postgraduate Diploma in Data Science in Health and Climate Change for Social Impact to address critical challenges at the intersection of data science, climate change, and health. The programme reflects the university’s commitment to fostering interdisciplinary solutions and preparing learners to address real-world problems through the purposeful use of data. Key inspirations for the programme included:
- Interdisciplinary Training: Offering foundational and advanced data science skills to participants from diverse academic and professional backgrounds including climate scientists, clinicians, public health experts, and professionals working in NGOs, public and private sectors.
- Inclusivity and Collaboration: Engaging a wide range of learners, including those from marginalised communities, and promoting collaboration across sectors.
- Real World Case Studies: The participants were exposed to real-world datasets and problem statements that require critical thinking and skills in integrating heterogenous datasets, simplifying complexity and modeling with a focus on explainability and interpretability to aid decision-making.
- Social Impact Focus: Addressing societal challenges, such as climate resilience and public health, through data-driven approaches.
- Addressing Data Collection Gaps: The curriculum emphasises identifying and addressing biases in data collection, using India-centric case studies to analyse societal disparities and foster innovative, ethical solutions for responsible and inclusive data curation.
Key Stakeholders Contributing to the Conception of the Programme
The programme was developed through collaborative efforts led by key academics from the department of computational biology and the department of social sciences and humanities.
The programme design benefitted from contributions by expertise of representatives from All India Institute of Medical Sciences (AIIMS), Indian Council for Medical Research (ICMR), (ARTPARK), India Health Fund, alongside other IDCA partners, including J-PAL SA, BITS Pilani, and data.org. The contributors convened twice to inform the programme design. J-PAL SA and ARTPARK also conducted interactive sessions with the learners and provided real-world case studies.
The Programme

The programme was designed for working professionals and implemented over 37 weeks in a hybrid format over two cohorts. Cohort 1 highlighted initial successes and challenges, while adjustments made for Cohort 2 significantly improved learner experience and outcomes.
The course structure emphasised a case-study approach, allowing learners to apply theoretical knowledge to real-world problems in health and climate. Key topics include:
Foundations of Data Science: Students began with an introduction to data science concepts, building a foundational understanding of the discipline.
Case Studies in Health and Climate: Students explored the application of data science to real-world challenges, categorised into three themes:
- Digital Health, OMICs and Health-Associated Case Studies: Examining intersections of healthcare and climate, focusing on themes like digitalisation, climate change and epidemics, antibiotic resistance, industrial pollution, and emergency conditions.
- Example: Building with global standards and terminologies to enable digital transformation of healthcare and its implementation in the Ayushman Bharat Digital Mission in India.
- Example: Developing models to guide surveillance and stewardship policies for antimicrobial resistance.
- Example: Predicting COVID-19 disease outcomes based on gut bacteria.
- Data-Driven Climate Sciences with Social Impact: Analysing how data science can address challenges in climate science, emphasising health and social outcomes.
- Example: Odd-Even vehicular traffic restriction policy in Delhi to reduce air pollution and its impact.
- Example: Integration of last-mile connectivity with public transit.
- Intersectionality and Representativeness in Data: Focusing on the implications of data diversity and equity in policy making, with an emphasis on social issues and innovative solutions.
- Example: Leveraging feminist perspectives for social impact in data sciences.
World-class syllabus and curriculum, coupled with the flexibility of online and offline modes, made the learning process engaging and impactful.”
Ashish Jha
Programme Participant
Topics and Skills Prioritised
Each topic and skill was chosen to provide participants with practical, interdisciplinary, and socially relevant expertise in data science.
Pedagogy Catering to Interdisciplinary Thinking
The programme fostered interdisciplinary thinking through:
Course Implementation
Feedback:
Used WhatsApp groups for instant communication and feedback and Google Forms for structured, bi-weekly feedback from learners to refine programme delivery.
Assessments:
- The course featured module-wise exams, replacing end-term exams to ensure better retention of concepts and progressive assessments.
- Capstone Projects: Participants worked on real-world challenges, such as optimising urban mobility or addressing healthcare disparities using data.
- Industry exposure was facilitated through guest lectures by ARTPARK experts, covering topics such as AI in healthcare and climate resilience.
- Weekly evaluations and adaptive teaching methods, such as introductory modules on Python and Excel, ensured learners from varied technical backgrounds could engage effectively.
Early Learnings from Implementing the Programme
Assignments were engaging, and the revised schedule allowed me to manage my work-life balance while learning.”
Prabhat Ranjan
Programme Participant
Diversity, Equity, and Inclusion Aspects
To increase diversity and representation in the programme, especially of women, members from marginalised communities, and people with disabilities, the following strategies were adopted:
Vision for Sustainability in the Future
IIIT-Delhi sees long-term value in the programme and will actively engage in raising funds for sustaining it. These fundraising activities will target donor support from philanthropic organisations and industry sponsorships. As a back-up, IIIT-Delhi may consider partial support to sustain future cohorts.
- Exploring industry partnerships to support scalability and ensure programme costs are covered.
- Considering fee adjustments to fully cover operational expenses while maintaining accessibility.
Any innovative programme requires flexibility as you learn on the go about how it can be improved. Adjustments such as introducing modular assessments and adapting schedules to accommodate working professionals highlight the need for adaptability in areas like curriculum design, learner support, and delivery mechanisms. However, integrating these flexibilities within the structured processes inherent in a public university revealed a key insight: fostering collaboration early, aligning programme goals with the university’s broader mission, and maintaining clear communication across stakeholders can turn the perceived rigidity of public systems into a structured foundation that supports creative, impactful initiatives. The concerns about diverse backgrounds of learners who may be unable to cope with the rigorous teaching standards of IIIT-Delhi were largely mitigated, especially through effective messaging, strong selection process and setting expectations.