Technology & digital skills

Technology skills with a practical purpose.

Choose the work you want to be able to do, then build a learning plan around it. Explore eight technology and digital learning paths, from software development and DevOps to data science and digital marketing.

These pages are learning and programme-selection guides. They do not advertise a confirmed intake. Availability, delivery format, entry requirements, fees, assessment and any funding route must be confirmed for a specific programme.

Ask about training availability

Start with the outcome.

A useful training brief describes what should change after the learning: a developer can deliver a tested feature, an operations team can explain a deployment, or a marketer can interpret a campaign without confusing activity with results.

Tell us whether you are exploring a career change, developing an existing role or planning learning for a team. The right starting point depends on experience, available study time and access to suitable practice work.

Define one task you want to perform independently.
Describe the knowledge and experience you already have.
Set a realistic practice schedule alongside work or other commitments.
Ask how feedback, support and assessment will work before committing.

Explore the learning paths.

Each guide sets out a distinct area of practice, a project to discuss and questions that help compare programmes. The topics reflect TechGeek's previously published training interests; the guidance has been rewritten for the current website.

AI engineering — Build and evaluate a useful AI workflow.
Cloud architecture — Understand the decisions behind a dependable cloud workload.
Cyber security — Practise identifying, investigating and explaining security risk.
Data science — Turn a business question into a reproducible analysis.
DevOps — Connect source control, testing, delivery and operational ownership.
Automation testing — Build reliable checks and useful defect evidence.
Full stack development — Follow a feature from browser interaction to stored data.
Digital marketing — Connect audience, content, conversion and measurement.

Ask for evidence of learning.

A list of software tools is not a learning outcome. Ask what you will make, how it will be reviewed and what you should be able to explain without following a tutorial.

For a team, choose a representative task with safe practice data. Agree a baseline and a review point, then check whether people can apply the skill to a second task. A portfolio can demonstrate work, but it does not guarantee employment or a particular salary.

Plan learning around the team's work.

For employer enquiries, describe the current systems, roles and recurring difficulties. A small, well-defined learning need is easier to assess than a request to make everyone an AI or cloud expert.

Separate skills development from a software delivery engagement. Training develops the team's ability to do the work; building an application has its own scope, acceptance criteria, support and commercial agreement.

Confirm the programme and the terms.

Before applying or paying, request the current syllabus, tutor or support arrangements, timetable, accessibility arrangements, cancellation terms and full cost. If a qualification is offered, ask who awards it and how achievement is assessed.

Do not assume that a technology course is a funded apprenticeship. Apprenticeship funding depends on the applicable rules and the circumstances of the programme, employer and learner. Confirm eligibility and the responsible training provider for the specific route.

There is no job, placement, salary or visa guarantee on these pages.
Any vendor examination, qualification, membership or external licence should be identified separately.
Use current written programme terms when deciding; historic promotional posts may no longer describe the offer.

Start with your
actual requirement.

Tell us the work, people and outcome you have in mind. We’ll confirm current scope and availability before agreeing the next step.