This course introduces students to modern cloud architectures and the emerging computing continuum spanning cloud, fog, and edge environments. It covers resource virtualization, distributed data management, serverless and container-based paradigms, and the deployment of AI/ML workloads across heterogeneous infrastructures. Students will explore key design principles such as scalability, elasticity, data locality, and energy efficiency, while gaining hands-on experience with contemporary cloud platforms and edge-to-cloud orchestration tools. The course prepares participants to design, manage, and optimize applications that operate seamlessly across the entire computing continuum.
This course provides a comprehensive introduction to modern big data processing models and systems, with a focus on scalable data workflows, stream processing, and real-time analytics. Students will explore core abstractions for dataflow programming, stateful stream processing, and distributed execution, with practical emphasis on Apache Flink and its ecosystem. The course combines theory with hands-on experience, guiding students through building and deploying end-to-end data pipelines for real-life applications. By the end of the course, participants will be able to design, optimize, and operate robust big data systems capable of handling high-volume, high-velocity data in production environments.
INSA Rennes: Big Data Algorithms – lectures and practical sessions (36h / year 2015 - 2025)
INSA Rennes: Big Data Storage and Processing – M1 – lectures and practical sessions (36h / year 2014 - 2025)
INSA Rennes: Introduction to Databases – L2 – lectures and practical sessions (68h / year 2012 - 2025)
ENS Rennes: Introduction to Java Programming – L3 – lectures (17h / year 2011 - 2015)
From 2006 to 2010, I gave several Master and Bachelor lectures and practical sessions on Distributed Systems, Communication Protocols and Distributed Algorithms at the Computer Science Department of University Politehnica of Bucharest