This course is available on the BSc in Actuarial Science and BSc in Mathematics, Statistics and Business. This course is available with permission as an outside option to students on other programmes where regulations permit and to General Course students.
This course is available on the BSc in Actuarial Science and BSc in Mathematics, Statistics and Business. This course is available with permission as an outside option to students on other programmes where regulations permit and to General Course students.
20 hours of lectures and 15 hours of seminars in the MT. Students are required to use their own laptops and install Python on their laptops.? Students not having a laptop of their own, which can be used for the purpose of the course, will be offered to use personal computers available in seminar rooms.
Students will be expected to produce 10 exercises in the MT. A set of exercises will be given in each teaching week.
Essential Reading:?? R. Elmasri and S. B. Navathe. Fundamentals of Database Systems, 7th Edition (Global Edition), Pearson, 2017. P. Lake and P. Crowther. Concise Guide to Databases: a practical introduction. Springer, Undergraduate Topics in Computer Science, 2013. J. Hellerstein and M. Stonebraker, Readings in Database Systems, 4th Edition, Morgan Kaufmann Series in Data Management Systems, 2005, http://www.redbook.io/ Additional Reading:? R. Ramakrishnan and J. Gerhke, Database Management Systems, 3rd Edition (International Edition), McGraw-Hill, 2002. C. J. Date, An Introduction to Database Systems, 8th Edition, Pearson, 2003. J. Leskovec, A. Rajaraman and J. Ullman, Mining of Massive Datasets, 3rd Edition, Cambridge University Press, 2018, http://www.mmds.org/ A. Meier and M. Kaufmann. SQL & NoSQL Databases: models, languages, consistency options and architectures for big data management. Springer Vieweg, 2019. K. Chodorow. MongoDB: the definitive guide. 2nd Edition, O?Reilly Media, 2013. I. Robinson and J. Webber and E. Eifrem. Graph Databases. O?Reilly, 2013.
Coursework (40%) in the MT. Project (60%). Students are required to hand in solutions to 4 sets of exercises, each accounting for 10% of the final assessment.? The project will require solving a practical task involving data model design, loading of data into a database, and querying the imported data in the database.