BioinformaticsUndergraduate

Linux & Biological Data

Develop the command-line skills needed to work efficiently with biological datasets and computational workflows.

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22 lessons5 weeks6 modulesUndergraduate
Course overview

Know what you are learning—and why.

Develop the command-line skills needed to work efficiently with biological datasets and computational workflows.

01
Structured progression

Move through topics in a logical order rather than learning isolated techniques.

02
Clear explanations

Build conceptual understanding before moving into procedures, calculations or code.

03
Applied practice

Reinforce learning through examples, exercises and practical applications.

04
Connected learning

See where this course fits within the wider Bioinformatics learning journey.

Skills you will build

Finish with capability, not just content watched.

The course is organised around the knowledge and practical abilities you should develop as you progress.

01
Linux

Develop this skill progressively through explanation, examples and application throughout the course.

02
Command line

Develop this skill progressively through explanation, examples and application throughout the course.

03
Text processing

Develop this skill progressively through explanation, examples and application throughout the course.

04
Workflow organisation

Develop this skill progressively through explanation, examples and application throughout the course.

Course curriculum

6 modules. One coherent journey.

Work through the curriculum in sequence to build a complete understanding of Linux & Biological Data.

01
Terminal foundationsConcepts · Examples · Practice
Module 1
02
Files and directoriesConcepts · Examples · Practice
Module 2
03
Pipes and redirectionConcepts · Examples · Practice
Module 3
04
Text processingConcepts · Examples · Practice
Module 4
05
Working with sequence filesConcepts · Examples · Practice
Module 5
06
Shell workflowsConcepts · Examples · Practice
Module 6
Before you start

University foundations

Some familiarity with basic quantitative reasoning is useful, but important concepts are developed carefully throughout the course.

01

Start where you are

No need to know everything

Use the course structure to identify gaps and build missing foundations progressively.

02

Work actively

Learning requires practice

Pause, calculate, code, explain and solve rather than treating lessons as passive video content.

03

Ask questions

Confusion is useful information

Identify exactly where your understanding breaks down and revisit the concept or seek expert help.

04

Apply it

Move beyond examples

Use the ideas in your own problems, assignments, projects, analyses or research.

Learning approach

From explanation to independent application.

The goal is not simply to finish lessons. The goal is to reach the point where you can use the ideas without being guided through every step.

01

Understand

Learn the idea

Start with intuitive explanation and build the underlying reasoning.

02

See it

Use examples and visuals

Connect abstract ideas to examples, diagrams, computation and interactive demonstrations.

03

Practise

Build fluency

Work through progressively more challenging questions and applications.

04

Apply

Work independently

Transfer your learning to examinations, code, projects, research or real datasets.

Explore interactive labs
Expert support

Stuck somewhere in the course?

Use 1-to-1 tutoring when you need a deeper explanation, feedback on your understanding, help with a related university topic or support applying the method to your own work.

The aim is not to finish Linux & Biological Data. The aim is to reach the point where you can use it.
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