Algorithms, data structures and computability

This module aims to help you become a computational problem solver. You’ll learn techniques to solve computational problems efficiently and apply those techniques using Python. You’ll also learn about the limitations of computing: which problems can’t be solved algorithmically or for which no efficient solutions are known. This module is suitable if – whatever your field – you need to implement an efficient algorithm or to understand both the power and the limitations of computing. Though the focus is on the underlying ideas, you’ll also work with some mathematical concepts and notation.

Modules count towards OU qualifications

OU qualifications are modular in structure; the credits from this undergraduate module could count towards a certificate of higher education, diploma of higher education, foundation degree or honours degree.

Browse qualifications in related subjects

Computing & IT qualifications
Open qualifications

Module

Module code

M269

Credits

Study level

Level of Study
OU	SCQF	FHEQ
2	9	5

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Module details Entry requirements Module registration Study materials

What you will study

You’ll learn to take a problem and state it precisely in order 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 really 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 what the limits are on the speed with which algorithms can solve many important practical problems.

The module comprises three parts, each ending with an assignment:

Part 1
In the first part, you’ll learn about the 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 are 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).

Vocational relevance

This module emphasises how valuable computational thinking skills are for solving a wide variety of real-world problems. Additionally, the study of computing concepts is tightly integrated with professional skills, such as testing and documenting Python programs and using Jupyter notebooks, and information literacy (in particular, searching for information and writing a brief report).

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.

Teaching and assessment

Support from your tutor

Throughout your module studies, you’ll get help and support from your assigned module tutor. They’ll help you by:

Marking your assignments (TMAs) and providing detailed feedback for you to improve.
Guiding you to additional learning resources.
Providing individual guidance, whether that’s for general study skills or specific module content.
Facilitating online discussions between your fellow students, in the dedicated module and tutor group forums.

Module tutors also run tutorials throughout the module. Where possible, recordings of online tutorials will be made available to students. While these tutorials won’t be compulsory for you to complete the module, you’re strongly encouraged to take part.

Assessment

The assessment details for this module can be found in the facts box.

Future availability

Algorithms, data structures and computability (M269) starts once a year – in October.

This page describes the module that will start in October 2025.

We expect it to start for the last time in October 2028.

Regulations

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.

Course work includes:; 3 Tutor-marked assignments (TMAs)
: No examination

Entry requirements

To enrol on M269 to start in October, you must have:

passed Introduction to computing and IT 2 (TM112) or be enrolled on it and have started it in April.

You need an understanding or experience of computing; an understanding and experience of programming in Python; and some knowledge of mathematics – check if you’re ready for M269, with our self-assessed quiz.

If you’re not sure you’re ready, talk to an adviser.

Register

Start	End	Fee
-	-	-	No current presentation - see Future availability
This module is expected to start for the last time in October 2028.

Additional Costs

Study costs

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.

Ways to pay for this module

Open University Student Budget Account

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:

Register now, pay later – OUSBA pays your module fee direct to the OU. You then repay OUSBA interest-free and in full just before your module starts. 0% APR representative. This option could give you the extra time you may need to secure the funding to repay OUSBA.
Pay by instalments – OUSBA calculates your monthly fee and number of instalments based on the cost of the module you are studying. APR 5.1% representative.

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.

Employer sponsorship

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.

More than one in ten OU students are sponsored by their employer, and 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.

Your employer just needs to complete a simple form to confirm how much they will be paying and we will invoice them.
You won’t need to get your employer to complete the form until after you’ve chosen your module.

Credit/debit card

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.

Mixed payments

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).

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 2025. Fees typically increase annually. For further information about the University's fee policy, visit our Fee Rules

This information was provided on 09/10/2024.

Can you study an Access module for free?

Depending on eligibility and availability of places, you could apply to study your Access module for free.

To qualify, you must:

be resident in England
have a household income of not more than £25,000 (or be in receipt of a qualifying benefit)
have not completed one year or more on any full-time undergraduate programme at FHEQ level 4 or above or successfully completed 30 credits or more of OU study within the last 10 years

How to apply to study an Access module for free

Once you've started the registration process, either online or over the phone, we'll contact you about your payment options. This will include instructions on how you can apply to study for free if you are eligible and funded places are still available.

If you're unsure if you meet the criteria to study for free, you can check with one of our friendly advisers on +44 (0)300 303 0069, or you can request a call back.

Not eligible to study for free?

Don't worry! We offer a choice of flexible ways to help spread the cost of your Access module. The most popular options include:

monthly payments through OUSBA
part-time tuition fee loan (you'll need to be registered on a qualification for this option)

To explore all the options available to you, visit Fees and Funding.

What's included

You’ll have access to a module website, which includes:

a week-by-week study planner
course-specific materials
audio and video content
assessment details, instructions and guidance
online tutorial access
access to student and tutor group forums.

The module is delivered entirely using Jupyter notebooks which includes the module text and the code for the examples and exercises. The material is also available in PDF and HTML format and the code is also available in separate Python files.

Computing requirements

You'll need broadband internet access and a desktop or laptop computer with an up-to-date version of Windows (10 or 11) or macOS Ventura or higher.

Additional requirements for this module:

5GB free disk space
Chrome, Firefox or Safari web browser (Microsoft Edge is not compatible with Jupyter).

To join in spoken conversations in tutorials we recommend a wired headset (headphones/earphones with a built-in microphone).

Our module websites comply with web standards and any modern browser is suitable for most activities.

Our OU Study mobile App will operate on all current, supported, versions of Android and iOS. It's not available on Kindle.

It's also possible to access some module materials on a mobile phone, tablet device or Chromebook, however, as you may be asked to install additional software or use certain applications, you'll also require a desktop or laptop as described above.

If you have a disability

The OU strives to make all aspects of study accessible to everyone and this Accessibility Statement outlines what studying M269 involves. You should use this information to inform your study preparations and any discussions with us about how we can meet your needs.

To find out more about what kind of support and adjustments might be available, contact us or visit our disability support pages.