Core module for Year 3 of programmes with Serbian/Croatian. This module enhances students' abilities to interpret and discuss works of Serbian, Croatian and Bosnian literature read in the original language. The reading list varies somewhat from year to year, but always covers about seventeen classic works.  The module provides a basis for further reading and is taught by weekly seminar-style classes with regular essay tutorials.

SERBIAN CROATIAN SERBIAN|LANGUAGE CROATIAN|LANGUAGE SERBO-CROATIAN

This module aims to provide a competent reading knowledge of Serbian/Croatian and basic communicative skills in the language. Students who complete the module...

New Language: Serbian and Croatian (SEES0034)

This module aims to provide a competent reading knowledge of Serbian/Croatian and basic communicative skills in the language. Students who complete the module successfully will be able to assure both potential employers and academic supervisors that they possess the necessary foundation-level Serbian/Croatian language skills to work with original Serbian/Croatian texts and to enable them to undertake study and/or research in Bosnia, Croatia, Montenegro and Serbia. The module provides an intensive introduction to Serbian/Croatian grammar, a knowledge of basic vocabulary, practice in the skills of oral communication in Serbian/Croatian in straightforward situations, translation and information retrieval skills, using Serbian/Croatian texts on regional as well as on international cultural, political, and social themes. The module is designed for beginners. It requires intensitve study including learning and practising independently beyond the contact hours.

This module builds on the quantitative methods modules of year 1 (Probability, Statistics and Modelling I) and year 2 (Probability, Statistics and Modelling...

Data Science for Crime Scientists (SECU0050)

This module builds on the quantitative methods modules of year 1 (Probability, Statistics and Modelling I) and year 2 (Probability, Statistics and Modelling II). It introduces data science techniques as a means for more sophisticated quantitative data analysis. This module aims to introduce students to computational methods for crime science. It consists of ten combined sessions (lectures + practical sessions). Practical sessions complement the lectures and enable the students to put the concepts into practice using the R programming language. In the practical sessions, the students will learn the skills necessary to conduct a full data science project. Lectures: The first part (web data collection) teaches the students how to collect data from online resources both through structured queries using APIs and through custom-made web-scraping. In the second part (text mining), the students learn how to handle messy text data and how to quantify and analyse this powerful type of data. The third part (machine learning) focuses on supervised and unsupervised machine learning where the students gain an understanding of the kinds of machine learning, the reporting and performance assessment of machine learning models, and commonly used algorithms. The module ends with two guest lectures by researchers working on advances on the intersection between data science and crime problems. The techniques covered in this module will be of relevance to students undertaking their final year independent research project. This module is suitable for those intending to start in data science positions.