37373 Programming for Data Analysis6cp; 4hpw, self-paced learning
Requisite(s): (37171 Introduction to Programming OR 41039 Programming 1)) AND (((33230 Mathematics 2 OR 33290 Statistics and Mathematics for Science OR 37132 Introduction to Mathematical Analysis and Modelling))
These requisites may not apply to students in certain courses. See access conditions.
Anti-requisite(s): 35383 Programming for Mathematical Modelling and Data Analysis
The goal of this subject is to introduce students to data structures and programming techniques that can be used to collect, manipulate, model, and analyse a broad range of datasets, including datasets with missing values. It uses the Python programming language to learn how to work with numerical, string, and more complex data formats, and to perform basic mathematical modelling or statistical analyses based on the data. The subject places a strong emphasis on developing a clear understanding of the common features of data structures from diverse areas, which may include nonlinear dynamics, discrete optimisation, mathematical physics, statistics, computational biology, or stochastic processes. Students develop practical skills in problem solving by working on a real-world data analysis project of their choosing, using publicly available datasets.
Autumn session, City campus
Detailed subject description.