This course aims to introduce the fundamental knowledge and hands-on skills of big data analytics in the field of media and communication. Special focus will be placed on techniques for searching, collecting, analysing, interpreting, and visualizing data. Technical details include, but not limited to, web crawling, data storage, data analysis, text mining, social network analysis, and data visualization, based on open source software packages. Through a variety of teaching learning activities, such as class demonstrations, individual exercises, quizzes, collaborative projects, and guest lectures, by the end of the semester, students are expected to become capable to collect big data from different data sources, i.e. social media harvesting, web scraping, online archiving or indexing data retrieving, with open source software packages. Students are also expected to produce socially, culturally, or commercially meaningful data-driven narrative outputs, such as data-driven journalistic report, data visualization, data-driven business analysis, and computational social science research reports. Meanwhile, critical reflection on the overuse and abuse of big data and relevant ethical and legal controversies will be discussed throughout the semester as well.