Modern applications such as electronic commerce, social networks, and location services are expecting efficient big data solutions. This course exposes practitioners to computational bottlenecks of processing, managing, and mining big data. It introduces a wide spectrum of advanced algorithmic techniques that underpin big data analytics and knowledge discovery. Learning advanced algorithms of big data will prepare students for a career as data scientists, and big data engineers. In particular, techniques to model and answer queries in streaming data are necessary skills for applications such as the Internet of Things. Algorithms to scale up machine learning models used in recommender systems or social network analytics are key algorithmic ingredients in big data analytics.
This is one of the core courses in the MProf Studs Data Science and Master of Data Science programs. Students of the Honours program and the Master of Information Technology can also participate in this course. There are no formal prerequisites required, but we recommend that students should already take COMPSCI 320 or relevant courses since it helps with the understanding and contextualization of the principles, techniques, and algorithm complexity covered in this course.