Reading lists for Computer and Data Science
Sample reading lists and recommended reading for some programmes in computer and data science have been provided by the Course Directors. Once teaching starts, your programme/module will provide you with full a reading list for the term.
MSc Artificial Intelligence
MSc Business Systems Analysis and Design
MSc Computer Games Technology
MSc Cyber Security
MSc Data Science
The following is some reading that will set up the first term's modules.
- General Introduction: Dhar, Vasant. "Data science and prediction." Communications of the ACM, 56.12 (2013): 64-73. https://cacm.acm.org/magazines/2013/12/169933-data-science-and-prediction/abstract
- INM430 Principles of Data Science: Cathy O'Neil and Rachel Schutt. Doing Data Science: Straight Talk from the Frontline. http://shop.oreilly.com/product/0636920028529.do
- INM433 Visual Analytics: Keim, Kohlhammer, Ellis, Mansmann: Mastering the Information Age Solving Problems with Visual Analytics. Eurographics 2010. http://www.vismaster.eu/wp-content/uploads/2010/11/VisMaster-book-lowres.pdf Chapters 1, 2 and 5.
- INM431 Machine Learning: Christopher Bishop: Pattern Recognition and Machine Learning. Springer 2006. http://www.springer.com/gp/book/9780387310732
- INM432 Big Data: Jure Leskovec, Anand Rajaraman, Jeff Ullman: Mining of Massive Datasets. Cambridge University Press 2014. http://mmds.org Chapters 1.