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Description
This module aims to teach basic concepts of programming using Python, complementing STAT0004 by focusing more generally on algorithms and programming logic with illustrative algorithms for data manipulation, and also introducing concepts that aid software engineering and effective computation, such as notions of error handling and object-oriented programming. It is intended for students registered on the undergraduate degree programmes offered by the Department of Statistical Science.听For these students, the academic prerequisites for this module are satisfied via successful admission to their programme.
Intended Learning Outcomes
- be able to make effective use of a Python programming environment;
- be able to听produce algorithms for basic data science tasks, with a respective implementation in Python;
- be able to听productively organise code and make use of existing libraries;
- develop a general understanding of procedural and object-oriented programming that goes beyond just Python coding.
Applications - An understanding of computational thinking, and in particular an ability to program, are essential skills for data scientists. This module introduces techniques that will provide students with a solid basis for conducting practical data analyses in a wide variety of application areas.
Indicative Content - Introduction to Python. Elementary data types, arrays and matrices, principles of data manipulation. Control structures: if/then, loops. Illustrative numerical and string manipulation algorithms. Functions, packages and scope. Debugging and exception handling. Built-in data structures: Python collections. File handling. Examples of packages for data science: pandas and numpy. Principles of object-oriented programming.
Key Texts - Available from .
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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