For over twenty years UNISCA has organised Model United Nation’s, hosting students from all over the world. We offer students a unique opportunity to take part in intense, yet intimate debate and to listen to a diverse group of speakers that have expertise over a wide range of relevant topics. Also, the program is complemented by a social activity every night. The Summer Course will be held in Amsterdam; a stunning city with a rich history, highly diverse population and an exciting nightlife! In short, UNISCA combines an invaluable academic opportunity with the possibility to expand your network with students from all over the world. Apply now for an unforgettable experience and enjoy all that our MUN and Amsterdam has to offer. Are you ready to unmask the political?
For more than fifty years Columbia Law School has offered this Summer Program in American Law in collaboration with the law faculties of Amsterdam and Leiden Universities. The Program is held every summer, for the whole month of July, and alternates each year between Amsterdam and Leiden. This year the Program will be held in Amsterdam. Recent students - and students from many years past - have given overwhelmingly enthusiastic evaluations of the Program. Former students - who are now distinguished judges, political leaders, senior attorneys, business executives, and law professors - participate in great numbers in formal Program reunions and in smaller informal reunions in many countries. The program is entirely taught by Columbia professors, and is designed to provide a general introduction to the American legal system for lawyers and other (legal) professionals, or (graduate) students interested in the program. Besides the excellent educational aspects, the Columbia Summer Program is also known for its exceptional fine atmosphere amongst participants and professors from Columbia University. The bonds summer students form with professors are strengthened outside the classroom, through daily lunches at the university and social activities. Hans Smit established the program with this collegial atmosphere in mind.
“Computer science is no more about computers than astronomy is about telescopes” – Edsger W. Dijkstra. Interaction with computers has become a big part of our daily life, but they do much more than help us with practicalities. They are tools for understanding the fundamentals of information, processes and human thinking. The insights they have brought us are some of the most important in human history, with far-reaching consequences for society. WHO SHOULD JOIN? Any student or professional who feels that computing is so important in today’s world that they should know its basics and understand its implications for science and society. No programming or mathematical knowledge is assumed. It may also be informative for those with a programming background, but covers material they will already be familiar with. If you have doubts about your eligibility for the course, please let us know. Our courses are multi-disciplinary and therefore are open to students and professionals with a wide variety of backgrounds. COURSE CONTENT On this course you learn to look with the eyes of a computer scientist, to understand the potential and limitations of computing and to apply these insights to such topics as social networks, biological processes, language and consciousness. Specific subjects we investigate are: • The science of algorithms, their power, universality and limits. This includes some programming, but for the most part you explore algorithmics away from the computer. • The science of data: encoding, compression and pattern recognition. • Taming complexity: dividing the problem, the search as a general heuristic and quantum computing. • Computing and philosophy: the ethics of big data and AI, free will and consciousness. • Have an informed discussion on ethical issues around big data and AI LEARNING OBJECTIVES At the end of this course, you: Understand the possibilities – and limitations – of computing, and how they shape our world, our organizations and our thinking. Can apply computational thinking in a range of areas, even ones apparently unrelated to computing. Can interact knowledgeably with programmers and other IT specialists. EXCURSION Visiting an event at the Waag Society (details determined when their summer programme is released)
With the increasing use of alternative software packages like R in data analysis, now is the time to learn their ins and outs. The large number of active programmers creating R packages makes this an up-to-date programme providing a huge range of statistical analyses. Researchers also use R to write functions for analysing data, or to create professional plots. WHO SHOULD JOIN? A completed undergraduate course in statistics and an acquaintance with basic linear algebra, the fundamentals of hypothesis testing, linear regression analysis and statistical tests such as the t-test. Nonetheless, we will briefly go over these topics again to refresh the memory. Affinity with programming is an advantage in learning R. You should bring a computer on which R (latest version) and R desktop (latest version) is installed. We will do all the exercises in a normal room where you will exclusively work on your own computer. If you have doubts about your eligibility for the course, please let us know. Our courses are multi-disciplinary and therefore are open to participants with a wide variety of backgrounds. COURSE CONTENT This course focuses upon understanding statistical models and analysing the results whilst learning to work with R. As well as introducing the software to newcomers, it presents basic and more advanced statistics. We start with descriptive statistics and visual representation of data, which is the first step for most statistical analyses. We then introduce the linear regression model, a widely used model with two main purposes: modeling relationships among the data and predicting future observations. After that we will extend the linear model to the generalized linear framework, in order to analyse non-normally distributed variables. In the second week we focus on a common problem in statistics: classification. We explore the two main areas of classification (supervised learning and unsupervised learning) with theory and examples. Every day consists of short lectures with examples, and exercises in which you apply what you have learned right away. Each week you are supposed to make an assignment which is graded. The focus in the exercises and assignment is the coding in R and how to apply and to interpret generalized linear regression models. By the end of the two weeks you are acquainted with various popular R packages, can write your own functions and can use attractive plots to present your data. EXCURSIONS Optional tour of “new” Amsterdam, rounded off with a drink. LEARNING OBJECTIVES Upon successful completion of the course, students will be able to: evaluate the quality of quantitative data sources choose the appropriate method for analysis, depending on the data source conduct various statistical tests analyze data using generalized linear framework handle multivariate data and classify them into categories have developed their skills in programming ABOUT THE PROFESSOR Andrea Bassi holds a MSc in Engineering Mathematics (Polytechnic University of Milan), with a focus on Applied Statistics. After having worked in Italy as a statistical consultant, he started his PhD training in Biostatistics at the VU University Medical Center, on the BIOMARKER project. The goal of this project is to design a Bayesian adaptive clinical trial to decide on the optimal targeted treatment strategy for patients with diffuse large B-cell lymphoma (DLBCL). Furthermore, Andrea collaborates with the VU University as a teaching assistant in the area of biostatistics, for bachelor and master programs. His main research interests are Bayesian statistics, statistical programming and decision theory. "Students should apply for Data analysis in R to discover the enormous potential of the open-source programming language R and for acquiring a series of skills and tools to analyze statistical problems of diverse nature." COURSE READINGS Readings to be provided at the start of the course. For those want to make a start on R: http://tryr.codeschool.com/. ADDITIONAL ENTRY REQUIREMENTS A completed undergraduate course in statistics and an acquaintance with basic linear algebra, the fundamentals of hypothesis testing, linear regression analysis and statistical tests such as the t-test. STUDENT EXPERIENCE "I think this is an important course to take because in the 21st century Data is power. You see companies such as google and Facebook that do a lot of data collection and to make use of that data you have to analyze it, so this is a good course to introduce those techniques. It's interesting because the Dutch have historically been aware of the importance of analyzing data. During the Golden Era, one of the reasons the Dutch East India company had such strong cartographers (map makers), and what they did was they had these cartographers travel and explore. Collecting data for future traders so that they could know the best spots to trade and that's how they used data during that time to advance their business. The importance of data has only grown today, whether you're running a technological company or a marketing company and therefore I found the course very practical." -Bernard Wong