XClose

UCL Module Catalogue

Home
Menu

Computational Thinking (MSIN0023)

Key information

Faculty
Faculty of Engineering Sciences
Teaching department
UCL School of Management
Credit value
15
Restrictions
Module is only available to students on the BSc/MSci Management Science year 2

Alternative credit options

There are no alternative credit options available for this module.

Description

This module introduces students to algorithms and how they programmed and used in a management context. Algorithms describe how problems can be solved using sequences of instructions, selection rules, iterative processes and control abstractions. This module is concerned with understanding how algorithmic software is designed to solve problems and how thinking in this way can help structure and solve problems generally. Students will learn to program in Python as a tool to aid understanding algorithm design.

 

Students will be introduced to a range of algorithms, including exhaustive and heuristic AI search algorithms, mathematical optimisation algorithms (linear programming), and stocastic algorithms, including Monte Carlo simulations. We will also be formalising and coding some of the matrix-based and machine learning algorithms that the students have already studied in Mathematical Foundations of Management II and in Data Analytics I.

 

This module will also introduce students to analysing the complexity of algorithms and the time required to complete computations. This will introduce important concepts to understanding the challenges and limits of processing big data.

 

Module deliveries for 2020/21 academic year

Intended teaching term: Term 1     Undergraduate (FHEQ Level 5)

Teaching and assessment

Mode of study
Face-to-face
Methods of assessment
60% Project (2,000 words plus code)
20% One essay (2,000 words)
20% Group video presentation
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
81
Module leader
Dr Andrew Whiter
Who to contact for more information
mgmt-undergraduate@ucl.ac.uk

Last updated

This module description was last updated on 5th March 2020.