This is a project-based course to expose students to both the theory and practice of cloud computing. The learning objectives include understanding of key principles of cloud computing concepts, models, technologies and its application for big data. The course is divided into two parts: two 3-hr lecture that introduces basic cloud computing concepts, models and technologies, and a project to develop web-based big data cloud applications augmented with four 2-hr project related lectures.

I. Topics include: principles of cloud computing – what and why, key business drivers, basic concepts and terminology, technical and non-technical challenges; fundamental concepts and models – cloud characteristics, cloud service (delivery) models, reference architecture, cloud deployment models; technologies behind cloud computing – resource hosting, main components in a datacenter, virtualization, multitenancy; cloud architecture – how to organize (partition) resources, how to operate/manage resources to meet certain objectives, cloud bursting; cloud applications and paradigms – cloud applications, challenges in developing applications, application development models – IaaS (Infrastructure as a Service), PaaS (Platform as a Service) and SaaS (Software as a Service), MapReduce programming model.

II. Cloud-based Big Data Projects - The learning outcome of the team-project is to design a big data application and to develop its implementation on a public cloud. A hackathon-like approach will be adopted to allow students to suggest ideas and form teams based on individual interests and skills. Four 2-hr lectures cover programming PaaS and SaaS IBM cloud services and pattern-based approach to design and implement big data applications. Students learn by examples with hands-on laboratories. For data, students can tap on the rich Singapore Smart Nation Open Government Data repositories among others.