Coding

MSc ASDS Preliminary Reading List

If you wish to do some preliminary reading in advance of your MSc, please see below for the recommended reading. For more detailed reading list for each Methodology course see 2019/20 Course Guides online. Please note that you are not expected to read any or all of these books before arriving but they will feature on your reading lists.

A Agresti and B Finlay Statistical Methods for the Social Sciences (Pearson, 2009. A course pack will be available for download online and can be purchased as a hard copy. Additional reading will be recommended)

A Agresti and C Franklin Statistics: The Art and Science of Learning from Data (Pearson, 2009)

G Bishop Pattern Recognition and Machine Learning (Springer-Verlag, 2006)

C Churcher Beginning Database Design: From Novice to Professional (Apress, 2007)

J Duckett HTML and CSS: Design and Build Websites (New York: Wiley, 2011)

A Géron Hands-on Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems (O'Reilly Media, 2017)

GitHub Guides at https://guides.github.com, including: “Understanding the GitHub Flow”, “Hello World”, and “Getting Started with GitHub Pages”.

P Gries, J Campbell and J M Montojo Practical Programming: An Introduction to Computer Science Using Python 3 (The Pragmatic Bookshelf, 2013)

G Grolemund Hands-On Programming with R (O'Reilly, 2014)

G Grolemund and H Wickham R for Data Science (O'Reilly, 2016. http://r4ds.had.co.nz)

J V Guttag Introduction to Computation and Programming Using Python: With Application to Understanding Data (IT Press, 2016)

T Hastie, R Tibshirani, and J Friedman The Elements of Statistical Learning: Data Mining, Inference and Prediction (Springer, 2009. Available online at http://statweb.stanford.edu/~tibs/ElemStatLearn/index.html

D Jacobson APIs: A Strategy Guide (O'Reilly, 2012)

G James, D Witten, T Hastie and R Tibshirani An Introduction to Statistical Learning (Springer, 2014. Available online at http://www-bcf.usc.edu/~gareth/ISL/)

P Lake Concise Guide to Databases: A Practical Introduction (Springer, 2013)

K London Developing Large Web Applications: Producing Code That Can Grow and Thrive (O'Reilly, 2010)

M Lutz Learning Python (O'Reilly, 2013. Intermediate and advanced documentation at https://www.python.org/doc/)

A C Müller and S Guido Introduction to Machine Learning with Python: A Guide for Data Scientists (O'Reilly Media, 2016)

T Nield Getting Started with SQL: A hands-on approach for beginners (O’Reilly, 2016)

C Robson and K McCartan Real World Research (London: John Wiley, 2015)

S M Tahaghoghi and H E Williams Learning MySQL (O'Reilly, 2006)

H Wickham Advanced R (Chapma & Hall/CRC, 2014)