Module manager: Dr Aleksandar Demic
Email: a.demic@leeds.ac.uk
Taught: Semesters 1 & 2 (Sep to Jun) View Timetable
Year running 2025/26
Acceptance onto the BEng/MEng Electronics and Computer Engineering, or BEng/MEng Mechatronics and Robotics Engineering programme
This module is not approved as a discovery module
This module provides an introduction to core aspects of computing essential for modern engineering and applied artificial intelligence practice. It is intended to give students a good grasp of a contemporary programming language and principles in algorithms and data structures, which are essential to designing, implementing and evaluating software and algorithms in problem solving.
The module has the following objectives:
- To provide a hands-on approach to the study of core topics in computing for modern engineering and applied artificial intelligence practice.
- To develop an understanding of the implementation of different data structures and algorithms with Python
- To learn how to apply different data structures and algorithms with Python
- To analyse the performance of different data structures and algorithms in different problem-solving contexts.
On successful completion of the module students will have demonstrated the following learning outcomes:
1. Apply basic knowledge of mathematics, statistics, and engineering principles to the solution of well-defined computing problems.
2. Analyse well-defined computing problems to reach substantiated conclusions using first principles of mathematics, statistics, and engineering principles.
3. Apply appropriate computational and analytical techniques to model well-defined computing problems.
Skills learning outcomes
On successful completion of the module students will have demonstrated the following skills:
a) Application of science, mathematics and/or engineering principles
b) Problem analysis
c) Application of computational and analytical techniques
* Fundamental of Software Design
* Introduction to Programming with Python
* Introduction to Data Analysis using Python
* Fundamentals of Algorithms
* Data Structure and Algorithms
* Fundamentals of Graphs and associated Algorithms
* Time series data processing on MCUs
* Application of Algorithms such as sorting, hashing etc.
* Performance Analysis of Algorithms (complexity, energy consumption etc.)
* Graph and Optimisation algorithms
* Case-studies applying the learnt knowledge
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Example Class | 8 | 1 | 8 |
| Consultation | 16 | 1 | 16 |
| Lectures | 4 | 1 | 4 |
| Practicals | 16 | 2 | 32 |
| Independent online learning hours | 30 | ||
| Private study hours | 110 | ||
| Total Contact hours | 60 | ||
| Total hours (100hr per 10 credits) | 200 | ||
Students studying ELEC modules will receive formative feedback in a variety of ways, which may include the use of self-test quizzes on Minerva, practice questions/worked examples and (where appropriate) through verbal interaction with teaching staff and/or post-graduate demonstrators.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| In-course Assessment | Class Test 1 | 30 |
| In-course Assessment | Class Test 2 | 30 |
| In-course Assessment | Coursework | 40 |
| Total percentage (Assessment Coursework) | 100 | |
Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated
There is no reading list for this module
Last updated: 30/04/2025
Errors, omissions, failed links etc should be notified to the Catalogue Team