Join a booming, in-demand field with a Master’s degree in Machine Learning and Data Science from one of the top 10 universities in the world. In this programme delivered by the Department of Mathematics at Imperial College London, you will develop an in-depth understanding of machine learning methods, alongside invaluable practical skills and guided experience in applying them to real-world problems. The curriculum is designed to propel your engineering or data science career forward, allowing you to choose the path that’s right for you, be that a role as a data scientist, a machine learning engineer, or a computational statistician.
With hands-on projects, you’ll build a portfolio to showcase your new skills in everything from probabilistic modeling, deep learning, unstructured data processing and anomaly detection. You will not only build a strong foundation in Mathematics and Statistics, giving you confidence in your analytical skills, but you will also acquire expertise in implementing scalable machine learning solutions using industry-standard tools such as PySpark, ensuring that no data is too big or too complex for you. You will also have the opportunity to broaden your horizons through one of the first of its kind study of ethical issues posed by machine learning. You will graduate with an ability to go beyond the algorithms and turn data into actionable insights, contribute to strategic decision making in your organisation and become a responsible member of this rapidly growing profession.
Imperial, ranked #10 in the world by Times Higher Education (2020 World University Ranking), is home to numerous eminent world-class researchers in machine learning, many of which will be contributing to this programme. It has had a rich history in driving innovation since the beginning of this field: John Nelder, Professor at Imperial College, helped developed GenSim, the precursor to R and the first proper implementation of a general framework for regression. The university maintains close ties with industry and a number of pioneering tech companies, some of which will be contributing to the programme by way of project ideas for your MSc thesis.
What makes this machine learning degree unique?
Imperial is home to world-famous mathematicians, including three winners of the Fields Medal, which recognizes outstanding mathematics achievement.
With one of the strongest and most awarded mathematics departments in the UK, Imperial produces deep thinkers capable of pioneering new research into today’s most pressing scientific and technological problems.
Unlike other master’s in data science programmes that teach Machine Learning with a computer science focus, this degree prepares students with the mathematical and statistical theory needed to truly understand machine learning, as well as the practical skills to deal with real world applications that they need to be successful in their careers.
The programme will train students in the mathematical, computational, and statistical foundations of machine learning, giving them the ability to critique data analysis and implement scalable machine learning solutions.
Students will also have the opportunity to broaden their horizons by participating in a programme-spanning module, the first of its kind, in ethics of machine learning and AI transparency, covering techniques to offset potential limitations and biases introduced by machine learning.
Average of 21 hours per week
Due to the circumstances of COVID-19, it was decided to delay the launch of the programme until October 2021. Applications are expected to reopen this Fall 2020.
If you already submitted an application for the programme, unfortunately your application cannot be deferred until the next academic year and will shortly be withdrawn. We would strongly encourage all academically eligible applicants to reapply for the October 2021 cohort.
Updates and further information can be located on the Imperial College London webpage.
If you have any questions about the admissions process or the programme, please do not hesitate to ask via firstname.lastname@example.org. The MLDS is delivered by the Department of Mathematics.
Applicants are expected to have a quantitative undergraduate degree in a subject like Mathematics, Computer Science, Statistics, Economics, or Physics to ensure there is an appropriate level of understanding to be best to cope with the demands of the programme.Learn more about Admissions
Study the mathematical, computational, and statistical foundations of machine learning, and pioneer new research into today’s most pressing scientific and technological problems. Over the two years of coursework, you complete twelve modules, including a research portfolio.Learn more about the curriculum
This degree prepares students to move their engineering or data science career forward across a wide variety of roles, such as a data scientist, machine learning engineer, or computational statistician.Learn more about Careers
The learning experience includes virtual live sessions and exercises with peers; interactive content consists of online assessment via quizzes, peer review; online individual and group presentations, written coursework and more.Learn more about Student Experience
Imperial is a global top ten university with a world-class reputation in science, engineering, business and medicine.Learn more about Imperial College London
Mathematics for Machine Learning and Statistical Analysis with R for Public Health are two Specializations on Coursera from other Imperial College programmes.Learn more how to try a course
The Machine Learning and Data Science master’s degree is a fully online degree part-time programme, delivered and structured over two-years, with three terms per academic year. You will complete twelve modules over two years, including a research portfolio. On average, you will dedicate 21 hours per week to study working toward key assessment deadlines and dates.
The majority of this time will be independent study- watching videos, reading core material, participating in discussion forums, and completing quizzes and peer reviews, though you can also expect to participate in weekly webinars, office hours, and Q&A sessions. These will be scheduled in advance to help you plan your study time around your other commitments.
The full and detailed learning schedule will be communicated before the programme starts. The online Machine Learning and Data Science MSc will hold it’s online ‘induction’ each year during the month of September.
The programme is offered on a part-time basis, over 24 months or two years.
No, your diploma will not state that this is an online degree.
This degree prepares students to move their engineering or data science career forward across a wide variety of roles, such as a data scientist, machine learning engineer, or computational statistician. Students will be trained to become deep thinkers, going beyond algorithms to turn data into actionable insights, contribute to strategic decision making, and become responsible, ethical members of this rapidly growing profession.
Yes. There will be regular office hours with programme team staff and Faculty members. Outside of this there will be scheduled sessions and webinars where you will have access to Faculty staff who will instruct and support your learning.
Yes, under the guidance of faculty advisors, you will be working with groups of fellow learners engaged in similar projects as you. As an Imperial graduate, you will join 200,000 alumni in an influential global community.
Yes, many of your instructors will be the same leaders from academic fields such as Statistics and Machine Learning that lecture on campus.
The Master of Machine Learning and Data Science programme will be delivered as a fully online degree. The Coursera learning platform allows learners to flexibly study around their own commitments, like employment, family, hobbies etc. The programme is designed in a way to allow learners to independently study for the majority of the programme, watching teaching sessions and returning to them around their daily schedule. There will be live and scheduled sessions, or group based work which require pre-organised attendance and engagement throughout. Assessments will also have deadlines and require learners to engage and submit when stated.
If you have any questions about the degree programme or admissions then please contact a member of the MLDS Support Team via email@example.com.
There is no on-campus programme for the Master of Machine Learning and Data Science degree at Imperial College London.
Students must take the assigned number of modules per term following the schedule below:
|Year||Term 1||Term 2||Term 3|
|Year 1||3 modules (12.5 ECTS)||2 modules (12.5 ECTS)||3 modules (15 ECTS)|
|Year 2||2 modules (15 ECTS)||3 modules (15 ECTS)||1 module* (20 ECTS)|
Note: Ethics module is split into 3 parts (T1,T3,T5)
Students will be required to complete twelve modules over two years, including a research portfolio.
No, the MLDS does not currently offer internships or placements within the degree programme structure.
Applicants are expected to have a quantitative undergraduate degree in a subject like Mathematics, Computer Science, Statistics, Economics, or Physics to ensure there is an appropriate level of understanding to be best to cope with the demands of the programme.
Applications will be considered for the programme based on the entry requirements, which will need to be met, but also the strength of their supporting statement, plus other work, research, or relevant experience.
Master’s level study is a progression from undergraduate work and is usually more specialised, interdisciplinary, or orientated to a specific profession. It is more intellectually demanding and challenging than undergraduate study. Students sometimes fail to appreciate the intense and demanding nature of Master's level programmes. There is no gradual introduction – the pace is fierce from the outset and it does not subside until the end. This requires a commitment to a sustained period of intensive work right from the start. In addition:
• the pace of lecturing is likely to be significantly faster
• you will be expected to undertake more directed background reading during the course
• you will be expected to arrive at solutions for yourself
For this reason the College requires a high academic standard of those seeking admission. International students, in particular, should also recognise the need to be proficient in English at the start of the course, hence the College's English language requirement.
Work experience is not essential but will be considered as part of the review process. Applications will be considered for the programme based on the entry requirements, which will need to be met, but also the strength of the supporting statement plus other work or relevant experience.
No, there is no admissions fee to pay to apply for the programme.
You will need to apply online directly with Imperial College London by registering and applying for the programme via https://imperialuk.elluciancrmrecruit.com/Apply/
• To show how you qualify for the programme you are applying for, you will need to provide information about the higher qualifications you have achieved or which you’re currently studying.
• All Imperial applicants must also show that they have a high-level of written and spoken English to meet the demands of our challenging academic environment. Find out more about English language requirements for postgraduate study.
• We can process your application more quickly if you upload scanned copies of the academic transcripts and certificates for the higher education qualifications you already hold when you apply.
• If you receive an offer we may ask you to provide evidence of your previous qualifications as part of the conditions of your offer. Where this applies, you must send the original physical documents by post).
• You will need to provide the names of two people who can provide an academic reference in support of your application. An academic reference could be from, for example: Your personal tutor, thesis supervisor, or line manager in a research group.
• One academic and one relevant professional reference may be acceptable – contact the relevant Admissions team for confirmation before you apply.
All candidates must demonstrate a minimum level of English language proficiency for admission to the College. For admission to this course, you must achieve the higher College requirement in the appropriate English language qualification. For details of the minimum grades required to achieve this requirement, please see the English language requirements for postgraduate applicants.
English Proficiency requirements are set at the Higher requirement with an IELTS score of 7.0 overall (minimum 6.5 in all elements).
The application portal will allow you to submit all transcripts and documents needed.
The academic requirement above is for applicants who hold or who are working towards a UK qualification. We also accept a wide variety of international qualifications. For guidance see our Country Index though please note that the standards listed here are the minimum for entry to the College. If you have any questions about admissions and the standard required for the qualification you hold or are currently studying then please contact the relevant admissions team.
United States export control regulations prevent Coursera from offering services and content to users in certain countries or regions. More information about which countries or regions are affected can be found on Coursera's website. Coursera must enforce these restrictions in order to remain in compliance with US law and, for that reason, we advise that all learners check this information before applying to the programme.
Coursera does not grant credit, and does not represent that any institution other than the degree granting institution will recognize the credit or credential awarded by the institution; the decision to grant, accept, or transfer credit is subject to the sole and absolute discretion of an educational institution. If upon graduation you intend to pursue a PhD or apply for employment which requires a master-level degree beyond 90 ECTS credits, we encourage you to investigate whether this programme meets your academic and/or professional needs before applying.