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ST340 Programming for Data Science

Lecturer(s): Professor Chenlei Leng

Prerequisite(s): ST221 Linear Statistical Modelling.

Commitment: 2 lectures and 1 computer laboratory per week. This module runs in Term 1.

Availability: Note that there is a cap on student numbers for this module. Pre-registration is essential and will open at 12 noon on 15th May 2019 for the 2019/20 academic year. Prioritisation will be given to students from Statistics department and those who have taken ST221, see the pre-registration page for details of the prioritisation rules and current status of allocations.

Content: In the modern world it is very easy to generate very large amounts of data. Capturing and exploiting the important information contained within such datasets poses a number of statistical challenges. It may not even be clear how much useful information the data contains. The module will cover a variety of algorithms developed to tackle some of these challenges.

Aims: To introduce students to algorithms suitable to the analysis of large datasets.

Objectives: At the end of the module, students should be able to implement various algorithms in the context of image analysis, handwriting recognition, personalized product suggestion, spam filtering and fraud detection.

Assessment: 50% coursework (three assignments) and 50% exam.

Deadline: Assignment 1: week 5, Assignment 2: week 8, Assignment 3: week 11.

​Feedback: ​Marked assignments will be returned within 2 weeks.

Examination period: Summer