Machine Learning and Data Science (Online)
  • Postgraduate taught, Online
  • MSc

Machine Learning and Data Science (Online)

Develop an in-depth understanding of machine learning models and learn to apply them to real-world problems.

Develop an in-depth understanding of machine learning models and learn to apply them to real-world problems

Benefit from flexible learning over 24 months on a fully online course

Build a portfolio and showcase your skills for a future career in mathematics, data or statistics

Course key facts

  • Qualification

    • MSc

  • Duration

    2 years

  • Start date

    October 2023

  • Study mode


  • Fees

    • £16,200 per year Home

    • £16,200 per year Overseas

  • Delivered by

  • Location

    • Online

Minimum entry standard 2023

  • 2:1 in statistics, mathematics, engineering, physics or computer science

View full entry requirements

Course overview

Accelerate your career in engineering or data science on this online and part-time Master's course.

Via hands-on projects, you'll build a portfolio in everything from probabilistic modelling and deep learning to unstructured data processing and anomaly detection.

This programme will enhance your analytical abilities in relation to mathematics and statistics. You'll gain expertise in tackling complex data by implementing scalable solutions using industry-standard tools, including PySpark.

You'll also consider the ethics and limitations of machine learning, and learn how to ethically apply these techniques to your work.

All learning is delivered online.


This page is updated regularly to reflect the latest version of the curriculum. However, this information is subject to change.

Find out more about potential course changes.

You’ll take all of these core modules

Core modules

You’ll also carry out an extensive research project focused on machine learning and data science.

This will see you undertake training in research on open-ended problems and demonstrate material taught over the programme. 

Research projects may be theoretical, methodological or applied depending on your interests. Work will be assessed by a written report and an oral examination.


Teaching and assessment

Balance of teaching and learning


  • Lectures and tutorials
  • Independent study

Year 1

  • 22% Lectures and tutorials
  • 78% Independent study

Year 2

  • 15% Lectures and tutorials
  • 85% Independent study

Teaching and learning methods

  • Blackboard virtual learning environment
    Virtual learning environment (Coursera)
  • Person at lectern giving speech
  • Tests
  • Four students sitting in a tutorial
  • Code on a computer screen
    Coding exercises
  • Reading
  • Discussion boards and prompts

Assessment methods

  • Person completing coursework
  • Multiple choice tests and online quizzes
  • Research project proposal document
    Research project
  • Oral examination
  • Papers from a written report
    Written report

Entry requirements

We consider all applicants on an individual basis, welcoming students from all over the world.

How to apply

Apply online

You can submit one application form per year of entry. You can choose up to two courses.

Application deadlines – Friday 26 May 2023

Tuition fees

Home fee

2023 entry


Overseas fee

2023 entry


Your future career

Robot hand

Prepare for advanced engineering roles in areas such as AI, data science and machine learning.

Lightbulb above a book

With specialised knowledge, you'll be highly sought after in a range of sectors.

Man standing under a sign pointing different directions

These include data scientists, machine learning engineers or computational statisticians.

Terms and conditions

There are some important pieces of information you should be aware of when applying to Imperial. These include key information about your tuition fees, funding, visas, accommodation and more.

Read our terms and conditions

You can find further information about your course, including degree classifications, regulations, progression and awards in the programme specification for your course.

Programme specifications