Essex Summer School in Social Science Data Analysis

Essex Summer School in Social Science Data Analysis is located in Colchester, United Kingdom on University of Essex Colchester Campus. Essex Summer School in Social Science Data Analysis is rated 3 out of 5 in the category graduate school in United Kingdom. The Essex Summer School in Social Science Data Analysis provides world-leading social science methods training to postgraduate research students by offering instruction from an internationally renowned faculty, drawn from many of the world’s top research institutions. It seeks to foster the academic research and careers of the postgraduate students who attend, both through training and by offering a unique networking and professional development experience. In doing so, we aim to contribute to the entirety of the international social science community. Each year, we receive nearly 600 students from all social science disciplines from over 40 countries seeking world-class instruction in social science research methods. Numerous alumni now hold academic positions throughout the world. Supervisors of postgraduate students in dozens of institutions routinely recommend the Essex SSDA Summer School as the premier methodology training experience for social science students. An Essex SSDA Summer School credential is recognised for its quality throughout the international academic social science community. Departments in all social science disciplines send students to the summer school to focus on building skills for basic research in social sciences. Each year, the school awards over 1500 ETC credits for use as part of post-graduate courses. In addition, the SSDA summer school offers a post-graduate degree, the MA in Social Science Data Analysis, which allows students to acquire and demonstrate a full range of research methods in the social sciences and to complete a supervised original research project. Complementing the research methods training offered by the summer school, the SSDA also functions as a professional networking opportunity. Machine Learning Network Analysis Maximum Likelihood Bayesian Methods R Programming Survey Methods Experimental Methods Ethnographic Methods Case Study Methods Quantitative Text Analysis Social Media Data Data Science