Inspiration to start the course and its alignment with the larger goals of the university
Ashoka University, known for its interdisciplinary education and societal focus, designed the Professional Executive Development Programme (PEDP) in Data Science for Social Impact to address the need for purpose-driven data professionals in India. The programme reflects Ashoka’s mission to drive systemic change by equipping individuals with skills to tackle complex societal challenges. Key inspirations for the programme included:
Bridging Technical Expertise and Impact: Addressing gaps between technical knowledge and social impact by training professionals to apply data-driven solutions to challenges like healthcare disparities and climate resilience.
Interdisciplinary Vision: Building on Ashoka’s liberal arts philosophy to integrate different domains.
Focus on Equity and Inclusion: Ensuring the programme is made available to learners at an affordable cost, through targeted scholarships.
The programme’s digital delivery through AshokaX, an online e-learning platform, expanded its reach, aligning with the university’s commitment to lifelong learning, offering opportunities for individuals of all ages and backgrounds to gain critical skills.
Key Stakeholders Contributing to the Conception of the Programme
Ashoka formed a Programme Design Committee (PDC) to guide the programme’s creation, fostering collaboration between internal leaders and external partners. This included academicians from the domains of health, climate change, data science and analytics as well as key leadership and operational staff members to ensure smooth delivery of the programme.
Key Contributions
Curriculum Design: Developed modules combining data science with social sector challenges, including health and climate.
Programme Assessment: Designed frameworks to evaluate learner outcomes and programme effectiveness.
Student Recruitment: Crafted outreach strategies emphasising diversity, equity, and inclusion.
Industry collaborators, such as J-PAL SA, BlueSky Analytics, and Khushi Baby, played an instrumental role in providing real-world case studies, datasets, and guest lectures. Their contributions helped contextualise theoretical learning within pressing social issues, such as climate resilience and public health. The programme brought together experts from the Centre for Climate Change and Sustainability, Centre for Data Science and Analytics and the Biosciences and Health research team to create a truly interdisciplinary curriculum.
Ashoka PEDP
The first part, comprising Courses 1 through 5, deals with the basic notions of computing with data followed by techniques and tools for collection, curation, collation, clustering, and classification that lead to solutions to problems in a given domain. Participants were also exposed to important approaches to analytics using statistical and machine learning algorithms. Courses in Part 1 include:
Data Science for Problem Solving
Data Management – Techniques & Tools
Data Analytics – Techniques & Tools
Geospatial & Time-Series Analytics
Data Visualisation & Interpretation
The second part, comprising Courses 6 through 9, deals with the issues, approaches, case studies, and hands-on projects in the climate and health sectors. Course 6 bridged the two segments, while Courses 7 and 8 enabled learners to scientifically analyse how Climate change affects the social and environmental determinants of health – clean air, safe drinking water, sufficient food and secure shelter. Course 9 explored the intersection of climate & health, issues of data governance and ethics, and brought out how data science can help in estimating, quantifying, and eventually mitigating threats. Courses in Part 2 include:
Evaluating the Impact of Urban Green Spaces on Heat-Related Illnesses in Bengaluru using satellite imagery, weather data, and Bengaluru OpenStreetMap Data for detailed information on the geography and layout of Bengaluru, including existing green spaces.
Climate Change and Nutritional Challenges in Tribal Communities of Jharkhand using weather data, rainfall data, and national health survey data.
Assessing the Impact of Cyclone-Induced Flooding on Waterborne Diseases in Coastal Odisha using health data, weather data, cyclone data, and satellite imagery.
Inspiration to start the course and its alignment with larger goals of the university Chanadanapriya Dhanraj
Indian Institute of Human Settlements
Topics and Skills Prioritised
Each topic and skill was carefully curated based on real-world applicability, ensuring participants are not only proficient in data science techniques but also capable of applying them in interdisciplinary and socially relevant contexts.
This module forms the heart of the programme, emphasising collaboration and community learning. It involves structured peer presentations where participants showcase their professional or academic work, fostering active engagement and cross-pollination of ideas. The module:
Builds confidence in public speaking and presenting data-driven narratives.
Encourages knowledge sharing across diverse sectors.
Increases visibility for learners’ work among key stakeholders.
Prioritised to ensure learners develop trust, accountability, and fairness in data use. This includes understanding algorithmic bias, privacy concerns, and ethical dilemmas in real-world scenarios.
A key focus is on teaching learners to analyse causal relationships rather than relying solely on correlations. This has practical applications in evaluating the success of policy interventions in areas like education and health.
Essential tools like QGIS equip learners to address spatial and temporal challenges, such as tracking climate change impacts or disease outbreaks.
These projects allow learners to work on real-world challenges. Sample projects include optimising water resource management and analysing health outcomes in marginalised communities.
Pedagogy Catering to Interdisciplinary Thinking
Ashoka’s interdisciplinarity ethos was embedded through:
Team-Based Assignments: Facilitating collaboration across diverse professional backgrounds.
Case-Based Learning: Using real-world challenges to foster critical thinking and interdisciplinary approaches.
Diverse Faculty Expertise: Drawing on expertise from public health, climate science, and data analytics.
Marketing and Outreach:
Strategic Channels and Methods
Targeted Outreach: Ashoka leveraged its alumni network, partnerships with NGOs, and social sector organisations to connect with potential participants. Webinars and email campaigns provided direct engagement opportunities, highlighting programme benefits.
Social Media Presence: Dynamic social media campaigns showcased programme highlights, including faculty profiles, cohort diversity, and application deadlines, significantly expanding the programme’s reach.
Special messaging targeted underrepresented groups such as women, rural professionals, and grassroots leaders, emphasising the programme’s commitment to accessibility and equity.
Programme Highlights Communicated
A programme website and a detailed prospectus outlined the programme’s objectives, structure, and interdisciplinary approach, acting as a key resource for prospective learners.
Social media graphics emphasised programme benefits, real-world applications, and testimonials from the inaugural cohort, building trust and credibility.
The marketing highlighted practical outcomes, such as the skills participants would gain, the interdisciplinary learning experience, and opportunities for impactful projects.
Fellowship opportunities and financial aid options were prominently featured to attract a diverse range of applicants, regardless of economic background.
The Learning Coordinators (LCs) played a vital role in delivering a learner-focused and impactful programme experience. The team consisted of five members with diverse expertise in fields such as computer science, data science, geospatial analysis, health and biosciences, and social impact. Two LCs transitioned from being learners in the first cohort, bringing unique insights to their roles. Their key contributions included:
Tailored Learning Support: Collaborating with faculty to design interactive labs, tutorials, and resources for participants of varying technical levels.
Peer Mentorship: Offering relatable guidance and practical strategies based on personal experiences.
Bridging Disciplines: Demonstrating interdisciplinary applications of data science in areas like climate resilience and public policy.
Fostering Engagement: Providing personalised office hours, active facilitation, and timely feedback.
Interactive live classes via Zoom, these sessions included real-time discussions and breakout rooms to encourage interaction.
An online Learning Management Software (LMS) hosted lecture recordings, assignments, quizzes, and discussion forums to support asynchronous learning.
Learners gained hands-on experience with virtual labs and tools:
AWS Cloud: Used for scalable data processing and analysis.
SmartLabs: Provided virtual environments for geospatial and time-series analytics.
Office Hours: Our key faculty and programme leads also took office hours to help learners come up to speed with the curriculum and feel comfortable with new topics.
WhatsApp Groups: Facilitated instant communication among participants, faculty, and coordinators for updates and doubt resolution.
Dedicated LCs: Five coordinators offered personalised support with grading, technical troubleshooting, and addressing queries.
Weekly practice assignments available on an online lab set-up in collaboration with Amazon Web Services; these were solved with support from dedicated LCs to address any queries and revise concepts.
Weekly quizzes, comprising multiple choice questions and short answers administered on a virtual learning management system.
Individual and group-based projects to assess the learners on end-to-end data-backed problem solving.
Proctored term-exams conducted during the middle of the term and end of the term.
Early Learnings from Implementing the Programme
The interdisciplinary approach and real-world case studies were highly praised.
Financial aid initiatives made the programme accessible to a diverse cohort.
Baseline Disparities: Varying levels of proficiency in data science and programming created challenges in maintaining a uniform pace.
Need for Differentiated Learning Paths: A single-track structure failed to meet the diverse needs of learners with varying technical competencies, leading to fragmented learning experiences between basic and advanced topics.
Time and Commitment: Participants struggled to balance programme demands with professional responsibilities, particularly managing the intensity of two projects simultaneously.
Technical Complexity: Advanced modules posed difficulties for learners new to technical fields, requiring additional support.
Skill Gaps in Fellowships: Feedback from partners like J-PAL SA highlighted the need for improved project management and stakeholder communication skills during the fellowship phase.
Introduced two learning tracks for learners to choose from:
Track 1: Data Science and Analytics – Focused on applying data science tools to solve social impact problems, targeting data practitioners and aspiring data scientists.
Track 2: Data Science for Social Impact Management – Focused on managing data-driven social impact projects, designed for generalists and non-technical professionals.
Enhanced Curriculum Design:
Introduced Delivering Social Impact Projects to develop stakeholder communication, project scoping, and evaluation skills.
Redesigned the healthcare course with integrated content and new contributors, while extending modules on healthcare and soft skills.
Integrated interdisciplinary concepts across courses for seamless learning.
Improved Accessibility and Support:
Added a four-week bridge course on Python and statistics to address foundational skill gaps.
Expanded the role of Learning Coordinators to provide personalised support.
Streamlined Workload:
Consolidated two projects into one, with interactive midterm assessments to ensure steady progress.
Simplified assignments to improve balance for working professionals.
Enhanced Capstone Experience:
Strengthened capstone projects with structured feedback and knowledge-sharing workshops involving peers, faculty, and external stakeholders.
Focus on Social Impact Projects: Early emphasis on practical applications connected technical concepts to real-world challenges.
Diversity, Equity, and Inclusion Aspects
Ashoka’s commitment to DEI was reflected in:
Efforts were made to reach underrepresented groups, including professionals from rural parts of India and women via visual communication and social media channels
Statement of purpose, background, relevance and an overall strong application was the focus, but additional consideration was given to gender, geography, and professional diversity.
All learners received either a partial or full scholarship to ensure no economic barriers hindered access.
The LCs collaborated with participants facing specific challenges to identify and implement solutions. For example, for a learner with low vision, course materials and slides were shared in advance, enabling better preparation and active participation. This adjustment also benefited the entire cohort by improving preparedness and managing the programme’s pace.
Some learners struggled to balance the programme’s intensity with personal and professional demands. The programme team, including the Programme Director, offered individualised support, addressing their concerns and creating tailored plans to help them stay engaged and complete the course successfully.
Vision for Sustainability in the Future
Launch self-paced certifications or short courses in specialised areas such as geospatial analytics and the interplay of climate and health. These offerings can cater to diverse learner needs by leveraging available recorded content and the programme’s modular design.
Incorporate course content and videos into upcoming courses offered by the Centre for Data Science and Analytics at Ashoka University. This modular approach allows for the creation of smaller, targeted courses focusing on core data science skills, climate change, health, and social impact, ensuring long-term value for the Ashoka community.
Reflections
Financial aid is often the first step toward fostering diversity, but true inclusivity requires much more—proactive accommodations, targeted outreach, and continuous iteration to meet the nuanced needs of underrepresented learners. A more effective approach lies in offering differentiated learning tracks that allows technical and non-technical learners to engage with content tailored to their needs. Learning Coordinators are critical as they provide personalised guidance, bridge gaps, support diverse learners, and ensure the programme delivers meaningful, impactful learning experiences.
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