MathematicsPostgraduate

Probability Theory

Build a rigorous understanding of random variables, convergence, expectation and foundational probability theory.

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34 lessons8 weeks7 modulesPostgraduate
Course overview

Know what you are learning—and why.

Build a rigorous understanding of random variables, convergence, expectation and foundational probability theory.

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 Mathematics 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
Probability spaces

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

02
Random variables

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

03
Expectation

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

04
Convergence

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

Course curriculum

7 modules. One coherent journey.

Work through the curriculum in sequence to build a complete understanding of Probability Theory.

01
Probability spacesConcepts · Examples · Practice
Module 1
02
Random variablesConcepts · Examples · Practice
Module 2
03
ExpectationConcepts · Examples · Practice
Module 3
04
Conditional expectationConcepts · Examples · Practice
Module 4
05
Modes of convergenceConcepts · Examples · Practice
Module 5
06
Limit theoremsConcepts · Examples · Practice
Module 6
07
ApplicationsConcepts · Examples · Practice
Module 7
Before you start

Advanced study

This course is best suited to learners with relevant undergraduate-level foundations or equivalent practical experience.

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 Probability Theory. The aim is to reach the point where you can use it.
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