Building Modern Data Pipelines for AI-Ready Systems

​We’re continuing our new workshop series in collaboration between GirlsWhoML and Mentor Me Collective, bringing together practitioners to make AI more accessible, practical, and career-relevant.

​This session focuses on the data layer behind modern AI systems — the part people often underestimate.

​Before a model can be useful, data needs to be collected, cleaned, structured, and delivered in a way the system can actually use. In this workshop, Avantika Chatterjee will explore why clean data matters more than raw scale, and how ETL pipelines, feature stores, and real-time vs batch processing shape practical AI and analytics systems.

​This session is ideal for students, early-career professionals, and career switchers interested in AI, data engineering, machine learning, cloud, or analytics.