IEEE Week 2026: Introduction to ML Pipelines & MLOps
October 6, 2026 · 1:30 PM - 3:30 PM @ Online event
Description
IEEE Week 2026: Introduction to ML Pipelines & MLOps was conducted online on 06 October 2026 as part of IEEE Week 2026. The webinar marked the inaugural technical event conducted by the newly initiated IEEE Computational Intelligence Society Student Branch Chapter of the University of Ruhuna , representing an important milestone in the chapter’s journey and its efforts to create learning opportunities in artificial intelligence, machine learning, and computational intelligence. The session was conducted by Kaveesha Chanduka, ML Engineer at Geek Labs and an engineering graduate of the University of Ruhuna . With experience in Machine Learning, Artificial Intelligence, and software development, the speaker shared both technical knowledge and practical industry experience with the participants. The webinar focused on Machine Learning Pipelines and Machine Learning Operations (MLOps) , introducing participants to the processes involved in moving machine learning solutions from experimental notebook-based development towards structured and production-oriented workflows. Participants were introduced to the concept of a machine learning pipeline and the different stages involved in developing and maintaining machine learning solutions, including data preparation, model training, evaluation, deployment, monitoring, and continuous improvement. The session also explored the role of MLOps in creating repeatable, maintainable, and reliable machine learning workflows. Participants gained exposure to concepts such as workflow automation, deployment practices, monitoring, model lifecycle management, and the importance of maintaining machine learning systems after deployment. A live coding demonstration provided a practical component to the webinar, allowing participants to observe how technical concepts discussed during the session could be applied in implementation. This helped bridge the gap between theoretical knowledge and real-world machine learning engineering practices. The speaker also shared insights from his professional experience in the machine learning industry, providing participants with a better understanding of industry workflows, practical challenges, and the skills required to work with real-world ML systems. The technical session concluded with an interactive Question and Answer session , allowing participants to clarify concepts and engage directly with the speaker. Approximately 100 participants attended the webinar, demonstrating strong student interest in Machine Learning, Artificial Intelligence, MLOps, and production-oriented ML technologies. As the inaugural event of the newly initiated IEEE Computational Intelligence Society Student Branch Chapter, the webinar established a strong foundation for future technical activities of the chapter. The event successfully connected academic knowledge with practical industry-oriented machine learning concepts while introducing the new chapter and its technical focus to the wider student community.
Agenda
7:00 PM – 7:05 PM Welcome and Introduction 7:05 PM – 7:15 PM Introduction to the Guest Speaker 7:15 PM – 8:15 PM Technical Session: Introduction to ML Pipelines and MLOps 8:15 PM – 8:35 PM Live Coding Demonstration 8:35 PM – 8:50 PM Question and Answer (Q&A) Session 8:50 PM – 8:55 PM Vote of Thanks 8:55 PM – 9:00 PM Closing Remarks and Group Photograph Guest Speaker: Kaveesha Chanduka Designation: ML Engineer, Geek Labs