Description de l'université Cours et Crédits Modalités de séjour
Description de l'université
Now in its 29th year, the LSE’s Summer School is the most well-established and the largest of its kind in the whole of Europe, with over 80 academically rigorous courses on offer. In 2016, nearly 6,000 students from 114 nations studied on the LSE campus in the heart of Central London.
Summer School aims to challenge and inspire students through direct engagement with our world-class faculty, with more than 270 full-time LSE academics teaching Summer School courses. During each three-week course students receive a minimum of 54 contact hours, generally including 36 hours of lectures and 18 hours of tutorial or seminar classes. Students will also have access to an Academic Tutor and the LSE Library during their time with us.
There are over 80 courses available at 3 different levels across 8 subject areas, and the full programme can be viewed on the LSE website. Each course is broadly equivalent to one semester from an undergraduate degree. Many institutions around the globe accept credit transfer for LSE Summer School courses. Generally our courses receive 3-4 credits in the US system and 7.5 ECTS in the European system.
We welcome a large number of postgraduate students and over 500 professionals to Summer School each year.
Cours et Credits
Liste des cours validés par Audencia, attention aux pré-requis : LSE cours Summer.pdf
Nouveaux cours pour 2019 :
EC203: Real Estate Economics and Finance (session one)
This course explores the theoretical and practical functioning of urban real estate markets using concepts from urban economics, finance and real estate economics.
ME315: Machine Learning in Practice (session one)
Machine learning is one of the leading data science methodologies for building prediction and decision frameworks using data. This course covers the theoretical foundation and application of a range of machine learning methods, both model-based and algorithmic. It is suitable for students from any discipline that uses data to inform decisions.
ME303: Statistical Methods for Multivariate Data in Social Science Research (session one)
Provides an overview of multivariate methods and then focuses on latent variable models and structural equation models for continuous and categorical observed variables, and their use in measurement and in modelling complex substantive hypothesis in the social sciences.
AC201: Performance measurement for decision making (session one)
Examines the use of financial and non-financial performance measures in complex organisational and managerial settings, with particular emphasis on their behavioural consequences, the design of performance and risk management systems and the benefits and limits of quantification.
ME310: Causal Inference for Experimental and Observational Studies (session three)
Provides an overview of a variety of modern techniques for studying cause and effect with social science data. Combining basic statistical theory, principles of smart research design, and hands-on experience with real data, this course will give students a basis for being good consumers and practitioners of modern quantitative social science.
Modalités de séjour
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