EVENTS

This workshop is designed to guide students through a clear and practical roadmap for building a successful career in Data Science and Artificial Intelligence. The session will cover essential skills, learning paths, industry expectations, project building strategies, and how students can leverage the NexGen Data Science Community for mentorship, hands-on experience, and career growth.

Nexgen, in collaboration with GDG On Campus MSIT, presents the Model Drift Workshop a hands-on session designed to help you understand why deployed machine learning models degrade over time. Learn the key causes of model drift, how it impacts real-world ML systems, and explore practical strategies for monitoring, mitigating drift, and maintaining high-performing models in production.

The session aimed to introduce participants to the rapidly evolving concept of Cloud and AI engineering roles at MAANG. The objective was to help attendees understand how to get into these roles and the skills required to succeed in them.

The session aimed to introduce participants to the rapidly evolving concept of Agentic AI—a transformative approach to building autonomous, goal-driven systems capable of reasoning, planning, and executing tasks independently. The objective was to help attendees understand how Agentic AI architectures are shaping the next generation of intelligent applications and to explore the tools, frameworks, and ethical considerations involved in designing such systems.

Throughout the virtual session, participants explored how SLMs challenge the dominance of large, cloud-based AI systems by offering a more efficient, private, and cost-effective alternative. Mr. Ghosal clearly explained the differences between Large Language Models (LLMs) — typically containing over 100 billion parameters — and Small Language Models (SLMs), which range between 1 million to 10 billion parameters. He emphasized how SLMs enable on-device AI processing, delivering faster responses, stronger data privacy, and dramatically lower computational requirements. The session sparked meaningful discussions and left attendees with a deeper understanding of how AI is becoming more accessible, adaptable, and localized.

The Barsat workshop focused on demonstrating the practical implementation and deployment of serverless architecture using AWS Lambda functions. Participants learned how to build event-driven applications without managing underlying infrastructure, specifically exploring how Lambda integrates with front-end applications to create scalable, cost-efficient API endpoints. The session provided hands-on exposure to modern cloud computing paradigms and the operational benefits of serverless computing models.

The SEQUEL: NoSQL Workshop was organized by the NexGen Data Science Community to help students understand the modern shift from traditional relational databases to NoSQL systems—the backbone of scalable, unstructured data management. The primary objective was to introduce participants to NoSQL concepts, data models, and real-world applications that power today’s high-performance, cloud-native systems.

The SEQUEL workshop was organized by the NexGen Data Science Community to strengthen students' foundational understanding of Structured Query Language (SQL) — the backbone of modern data management. The primary goal was to help participants gain hands-on experience in designing, querying, and managing databases, bridging theoretical knowledge with practical industry use.

The Atelier - Data Preprocessing Workshop was organized by NexGen, the official Data Science Community of MSIT, on 28th February 2025. The session was conducted by Srijon Sen, who currently serves as the Management Lead and Co-Lead of the Data Engineering and Computer Vision domains at NexGen..

The Data Trove session was organized to showcase the innovative projects developed by members of the NexGen Data Science Community, highlighting how theoretical concepts can be transformed into real-world applications. The event aimed to promote peer learning, collaboration, and practical exposure by allowing students to present their data-driven solutions to emerging technological challenges.

The purpose of this orientation was to introduce students to the NexGen Data Science Community — its vision, mission, and the range of opportunities it offers in the world of Data Science, AI, and technology innovation. The goal was to create awareness about how the community acts as a launchpad for skill development, collaboration, and networking among aspiring data scientists.