Master of Science in Machine Learning and Data Science
Imperial College London
Who is this degree for?
This degree offers multiple pathways to meet the needs of learners from a variety of backgrounds; for example, students just starting a career in data science and those already working in roles such as senior data analysts, bioinformatics scientists, statisticians, and data scientists.
Graduates are likely to pursue roles as data scientists, machine learning engineers, natural language processing engineers, data engineers, bioinformatics or health data scientists, AI engineers, or software engineers. Possibilities extend beyond this list, however, as machine learning is slowly becoming indispensable in other fields, such as journalism or tourism.
This is a rigorous programme; applicants are expected to have a quantitative undergraduate degree in a subject like computer science, math, statistics, economics, or physics.
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 programme, hence the College's English language requirement.
Cohorts and Deadlines
Application deadline: next application deadline to be announced.
The programme is offered once per year, in October.
Requirements for Admission
- At least a 2.1 UK Bachelor’s Degree in Statistics, Mathematics, Engineering or Physics. The academic requirement of a minimum 2.1 is for applicants who hold or who are working towards a UK qualification. For guidance on how qualifications awarded by non-UK institutions may satisfy the College’s minimum academic admission requirements - see Imperial's Country index.
- 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 (equivalent to IELTS 7.0). Find out more about our English language requirements for postgraduate study.
- Create an application via the Imperial College London ‘Apply’ webpage - this is where you will submit your application.
- Prepare the information you will need to complete your application, including:
1) personal statement,
2) academic transcript(s),
3) CV/resume, and
4) referee contact details.
We aim to review applications in detail once all information has been submitted. The process takes 6-8 weeks.
All documentation, including references and proof of English language proficiency, are mandatory. We are unable to make a decision on your application if we have not received your references, other supporting information related to qualifications or English language requirements, so it is important that you submit this information and documents in a timely manner via the Imperial College London online system.
For 2022 entry, Imperial have an application processing fee for MSc and MRes courses to help cover some of the administrative and staffing costs associated with processing the large volume of applications that Imperial receives. This fee will be £80.
Imperial will waive the fee for any applicant – Home or Overseas – who demonstrates that they are experiencing financial hardship. Please see Imperial's website for further information.
Questions about the admissions process or the programme? Please do not hesitate to ask via email@example.com.
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.