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This program integrates a variety of topics to allow students to learn the fundamental facets of big data and how it is used in the real world. Topics include mathematical foundations (convex/non-convex optimization and computational methods), data analytics (from data collection, integration, cleansing, mining, machine learning, to business intelligence), and data processing infrastructures (MapReduce, Hadoop, Apache Spark, SQL).
The courses in this program are offered by renowned faculty members from the Computer Science and Engineering Department and the Mathematics Department at HKUST. HKUST ranks at the 30th in Computer Science and Information Systems and 36th in Mathematics according to 2021 QS World University Rankings by Subject.
Overview
Syllabus
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Courses under this program:
Course 1: Foundations of Data AnalyticsLearn the fundamental techniques for data analytics and to be prepared for learning and applying more advanced big data technologies.
Course 2: Data Mining and Knowledge DiscoveryLearn how to discover knowledge in data via data mining.
Course 3: Big Data Computing with SparkLearn the theory and gain hands-on experience of big data systems, using Spark as the exemplary platform.
Course 4: Mathematical Methods for Data AnalysisLearn mathematical methods for data analysis including mathematical formulations and computational methods. Some well-known machine learning algorithms such as k-means are introduced in the examples.
Course 5: Big Data Technology Capstone ProjectThe Big Data Technology Capstone Project will allow you to apply the techniques and theory you have gained from the four courses in this MicroMasters program to a medium-scale project.
