The University of California at Berkeley will be offering a class on big data to its undergraduate and postgraduate students this year, focused specifically on data analysis as applied to the social networking site Twitter -- the perfect subject to study in relation to big data analysis.
The never-ending flow of information found on Twitter is a subject that students are more likely to relate to than other uses of big data -- including studying the origins of the universe or complex cloud computing systems.
In the company's first official partnership with a higher education institution, engineers from Twitter will advise students on the company itself, provide elements of source code and explain how popular websites can be related to advanced computing in big data.
How to store, process, analyze and make sense of Big Data is of increasing interest and importance to technology companies, a wide range of industries, and academic institutions. In this course, UC Berkeley professors and Twitter engineers will lecture on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter microblog data.
Topics will include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing. Social science perspectives on analyzing social media will also be covered.
For students talented in programming, exploring how the simple-looking service actually works behind the scenes is an incredible opportunity -- as well as a valuable addition to the CV of anyone interested in social media.