You’ll learn to state a problem precisely so that it can be solved with a computer. In other words, you’ll learn to express the problem in a way which allows you to write an algorithm for solving it. However, not all algorithms are equally good solutions. For that reason, you’ll also learn how to analyse the speed and efficiency of algorithms and establish whether an algorithm does what it is supposed to do. Finally, you’ll delve into the very foundations of computing. You’ll learn which problems cannot be solved with an algorithm. You’ll also learn the limits on the speed with which algorithms can solve many important practical problems.
The module comprises three parts, each ending with an assessment task:
Part 1
In the first part, you’ll learn basic data structures for organising data, like lists, stacks, queues, dictionaries, and sets. You’ll also learn how to analyse the complexity of an algorithm and how to measure its runtime.
Part 2
The second part covers two non-linear data structures: trees and graphs. The former can represent hierarchical data, and the latter can model social, transport, and other kinds of networks. The main focus of the second part is algorithmic techniques like search (brute-force, breadth-first, and depth-first), divide and conquer, recursion, and greedy algorithms. These are general-purpose techniques for solving a wide range of problems.
Part 3
In the third part, you’ll further develop your understanding of graphs and algorithmic techniques (backtracking, dynamic programming). You’ll also learn about the limitations of computational problem solving (non-computability and the P ≠ NP conjecture).
This module emphasises the value of computational thinking skills for solving a wide variety of real-world problems. Additionally, studying computing concepts is closely integrated with professional skills, such as testing and documenting Python programs, as well as using Jupyter notebooks.
If you’re aiming to become a programmer or system builder, this module is ideal as it covers topics and skills that many leading employers in IT and computing value highly, and check in technical interviews.
This module has been awarded a quality mark by the Royal Statistical Society, providing reassurance that the teaching, learning and assessment within this module is of high quality and meets the needs of students and employers.
You’ll get help and support from an assigned tutor throughout your module.
They’ll help by:
Online tutorials run throughout the module. While they’re not compulsory, we strongly encourage you to participate. Where possible, we’ll make recordings available.
Course work includes:
You’ll have access to a module website, which includes:
Additionally, the website includes:
You can work through the module materials online, on the Open Computing Lab (which requires internet access), or offline, on your computer (which requires installing the provided M269 software).
You can study this module on its own or use the credits you gain towards an Open University qualification.
M269 is a compulsory module in our:
M269 is an option module in our:
Algorithms, data structures and computability (M269) starts once a year – in October.
It will next start in October 2026.
We expect it to start for the last time in October 2028.
As a student of The Open University, you should be aware of the content of the academic regulations, which are available on our Student Policies and Regulations website.
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There may be extra costs on top of the tuition fee, such as set books, a computer and internet access.
If your income is not more than £25,000 or you receive a qualifying benefit, you might be eligible for help with some of these costs after your module has started.
There may be extra costs on top of the tuition fee, such as set books, a computer and internet access.
If your personal income is £25,000 or less, or you’re on certain benefits, you could qualify for a grant and OU top-up funding to cover 100% of your course fees. Apply online at the same time as you register on your module.
For more information on how to apply, visit our Part-Time Fee Grants for students in Scotland page.
The Open University Student Budget Accounts Ltd (OUSBA) offers a convenient 'pay as you go' option to pay your OU fees, which is a secure, quick and easy way to pay. Please note that The Open University works exclusively with OUSBA and is not able to offer you credit facilities from any other provider. All credit is subject to status and proof that you can afford the repayments.
You pay the OU through OUSBA in one of the following ways:
Joint loan applications
If you feel you would be unable to obtain an OUSBA loan on your own due to credit history or affordability issues, OUSBA offers the option to apply for a joint loan application with a third party. For example, your husband, wife, partner, parent, sibling or friend. In such cases, OUSBA will be required to carry out additional affordability checks separately and/or collectively for both joint applicants who will be jointly and severally liable for loan repayments.
As additional affordability checks are required when processing joint loan applications, unfortunately, an instant decision cannot be given. On average, the processing time for a joint loan application is five working days from receipt of the required documentation.
Read more about Open University Student Budget Accounts (OUSBA).
Studying with The Open University can boost your employability. OU courses are recognised and respected by employers for their excellence and the commitment they take to complete. They also value the skills that students learn and can apply in the workplace.
Over 30,000 employers have used the OU to develop staff so far. If the module you’ve chosen is geared towards your job or developing your career, you could approach your employer to see if they will sponsor you by paying some or all of the fees.
You can pay part or all of your tuition fees upfront with a debit or credit card when you register for each module.
We accept American Express, Mastercard, Visa and Visa Electron.
We know that sometimes you may want to combine payment options. For example, you may wish to pay part of your tuition fee with a debit card and pay the remainder in instalments through an Open University Student Budget Account (OUSBA).
We know that sometimes you may want to combine payment options. For example, you may get support from your employer to pay part of your tuition fee and pay the remainder by credit or debit card.
For more information about combining payment options, contact an adviser.
Please note: your permanent address/domicile will affect your fee status and, therefore, the fees you are charged and any financial support available to you. The fee information provided here is valid for modules starting before 31 July 2026. Fees typically increase annually. For further information about the University's fee policy, visit our Fee Rules.
