history of the book|textual cultures|medieval authorship|orality and literacy|digital humanities

Module Description: 

Modern readers usually encounter medieval texts in standard printed formats, but what about their original audiences? On this course...

Ink: Material Encounters with Medieval Texts (ELCS0015)

This is the dissertation module for the MA Policy Studies in Education programme. The Dissertation is 15,000 words and will be submitted on a topic negotiated...

Dissertation on Policy Studies in Education (EDPS0071)

This is the dissertation module for the MA Policy Studies in Education programme. The Dissertation is 15,000 words and will be submitted on a topic negotiated between the student and their tutor. It is intended that the writing of a Dissertation will offer an opportunity for the student to produce a piece of sustained writing, constituting critical theoretical/conceptual analysis as well as (in most cases) related empirical work, on a topic of direct interest to them.

It is a truism that we live in an information society and that this is a new and unprecedented state of affairs. The rediscovery and popularisation of...

Early Modern Information Culture, c.1450-1750 (CMII0022)

It is a truism that we live in an information society and that this is a new and unprecedented state of affairs. The rediscovery and popularisation of classical learning, the explosion of printed material, and the birth of a modern concept of scientiﬁc knowledge presented a challenge to scholars and states across Europe: how to organise, use, and share information in an age where there was – in the words of Ann Blair – “too much to know”.

This module gives you an introduction to all essential elements needed for health data scientists to use python as a powerful tool for analysis and scientific...

Programming with Python for Health Research (CHME0031)

This module gives you an introduction to all essential elements needed for health data scientists to use python as a powerful tool for analysis and scientific presentation of complex health related data. In this module you will learn how to construct reliable, readable, efficient analytical procedures for data-intensive research in a collaborative environment. You will be introduced to libraries, coding conventions, functional and object-oriented programming, visualisation, and version controlling, essential for reproducible research. The module will emphasise practical techniques and learning by doing, it is an intensive practical course, which will allow you to train a range of techniques that are essential for health data scientists.
 
At the end of the module you should be able to:
1.    Understand the fundamental principles of python programming, algorithms, including knowledge of the main data types and structures.
2.    Understand the use of conditionals and loops as well as the application of functions for code reproducibility
3.    Knowledge of key modules essential for data science including; numpy, pandas, re, and matplotlib  
4.    Perform basic statistics and data visualisation of complex health-related datasets
5.    Understanding the concepts of object-oriented programming, version controlling and high-performance computing.

Delivery Mode should be:
You will learn by a combination of lectures and practical problem classes and will therefore require a laptop that you can use to write python code, execute scripts, and connect to databases; tools we will use include Python 3. Anaconda, and Jupyter notebooks. Tablets are not suitable as they do not offer the necessary underlying infrastructure to install and run the needed software.

 