We hope that you and your loved ones remain well in these challenging times. 

We are writing to you in our capacity as Director of School of Public Health, Professor Deborah Ashby and MSc Health Data Analytics and Machine Learning Programme Co-Directors, Professor Paul Elliott and Dr Marc Chadeau-Hyam. You currently hold an offer from us to commence study on the MSc Health Data Analytics and Machine Learning programme in October 2020 and we are looking forward to welcoming you to the School of Public Health at the start of the new academic year. 

We are contacting you today with the final plans for our MSc Health Data Analytics and Machine Learning programme for the Academic year ahead. At all times, the programme will be subject to the requirements of the current UK Public Health guidance and College Health and Safety measures. 

The delivery of our programme for the next academic year will be a mix of online and blended/on-campus delivery. You can read more about what blended learning is below. 

Our Autumn term core teaching will be delivered fully online. There will be no core teaching scheduled on-campus for the Autumn term that requires you to be on-campus. 

For the spring term, we will continue with the blended learning model of delivery. You will access our high quality teaching materials online, through either Coursera or our internal Virtual Learning Environment (Blackboard), but if we are able to do so there will be on-campus scheduled teaching that will take place. Unless the UK or your home country public health guidance precludes it, you will be expected to be in the UK/London in the Spring Term and attend on-campus teaching from January onwards. 

Institutional guarantees 

All on campus provision will be subject to the requirements of the current Public Health advice from the UK Government, College guidelines on social distancing and any additional health and safety measures. In the event that there is an escalation of the current outbreak or a new outbreak of COVID-19 during your programme then, in line with Public Health Advice from the UK Government, we may be forced to suspend on-campus activity, which we hope to deliver in the Spring term. This may be in connection with either national or local requirements. Since we will already be delivering the taught elements of your programme remotely for the Autumn term, we will continue to be able to deliver these elements to all students remotely for the Spring term, if needed. 

The College will deliver your programme to ensure the approved learning outcomes are met and will take steps to make alternative arrangements in any extreme circumstances where this is not possible. The College is also developing community building activities to support the multi-mode experience for students. 

College-wide induction and enrolment activities will operate in a remote format at the start of the academic year and there will be no requirement to visit the campus in-person to begin your studies. 

We are also looking to host an optional on-campus induction activity, for students who are able to join in person. Further details will be shared about this in due course. 

Programme delivery 

Autumn term – fully online 

Our Autumn term core teaching will be delivered fully online. 

We will be scheduling some added value activities for those who are able to join us on-campus. Further information is available below. 

The scheduling of the live sessions for remote delivery will carefully consider the various time zones of students globally, as much as possible. This means that we will aim to alternate start times of the sessions from week to week, to allow students to join at least one live session for each module, each week. If students are not able to join a live session, all sessions will be recorded and accessible to watch shortly afterwards. Group work and tutor/practical groups will aim to consider students who can work/join such sessions based on similar timezones. 

Your Autumn term modules will be delivered through a combination of both the Coursera platform and our internal Virtual Learning environment, Blackboard. 

Spring term – blended delivery with on-campus attendance 

For the spring term, we will continue with the blended learning model of delivery. You will access our high quality teaching materials online, through either Coursera or our internal Virtual Learning Environment (Blackboard), but if we are able to do so there will be on-campus scheduled teaching that will take place. 

Unless the UK or your home country public health guidance precludes it, you will be expected to be in the UK/London in the Spring Term and attend on-campus teaching from January onwards. 

If you are unable to travel/be on-campus for the spring term, we will try to support/deliver teaching to individual students as best we can remotely (reviewing on a case by case basis). Whilst learning outcomes can be met, your student and learning experience is likely to be different (including the ability to join live teaching sessions) and therefore other options will be available. These options include, an interruption from studies (meaning you could return the following year to complete the remainder of your studies on campus), or you may be able to leave the programme and exit with a PG Certificate award if you have successfully completed 30ECTS. 

If we are unable to schedule any on-campus teaching, we have contingency plans in place in case of further disruption as a result of COVID19 and associated restrictions. 

Summer term – your project 

One of the key features and experiences for you on the programme will be your Research Project. For Term 3, we anticipate your Research projects will go ahead as planned and they are expected to run as normal in most reasonable scenarios. If there any UK restrictions, the vast majority of projects would be able to run as normal and could be conducted remotely with regular virtual meetings with your supervisors. 

You will spend 4 months dedicated on your research projects that are mostly drawn from active, ongoing research undertaken by Faculty, whilst there will be room you to propose you own project as well. 

 

Location 

On-campus teaching (if possible for the Spring term) is likely to be scheduled at the St Marys, Charing Cross and South Kensington campuses. 

Accessing the virtual learning environments 

Your Autumn term modules will be delivered through a combination of both the Coursera platform and our internal Virtual Learning environment, Blackboard. Your spring term modules will be delivered through our internal Virtual Learning environment, Blackboard. 

We have an established partnership with Coursera, in delivering online education as part of our School’s Digital Education Strategy. We are experienced in designing, developing an delivering high quality online education to students, which means you will have access to our high quality and carefully designed teaching materials through the Coursera platform for this programme. As an established and global learning provider, Coursera use engaging and innovative learning features to provide high quality degree learning experiences. Teaching and learning on the programme will be delivered through the Coursera platform using a range of methods including: 

· pre-recorded lectures and video capture 

· slide-decks with audio commentary 

· practical exercises in coding and analysis 

· asynchronous peer-to-peer and staff-moderated discussion forums 

· synchronous scheduled live tutorials/sessions via Zoom 

· discussion forums 

· discussion prompts 

Synchronous scheduled live tutorials/sessions via Zoom will take the form of interactive lectures where you will be given opportunities to ask questions live. 

You will be guided as part of the induction course and resources about the tools you will use and engage with as part of the teaching/delivery of the programmes. 

Learning experience and commitment 

We anticipate you will be able to complete the programme within the timescale previously advertised. 

As you aware the programme is a 1 year/full-time programme, which requires a consistent and dedicated commitment through the academic year. 

Our programme will be delivered via a blended learning model, this means that you will: 

· engage/work through online content/resources asynchronously and independently in your own time, approx. 2-4 hours per module, per teaching day. This time will vary from learner to learner and day to day. 

· attend scheduled live sessions via Zoom, approx. 2-3 hours per module, per teaching day. These live sessions will be a mix of synchronous live lectures/seminars and tutor groups. We will schedule these live sessions with consideration of global time zones for the Autumn term to try and ensure maximum participation. However, all live sessions will be recorded and accessible to students shortly after the session, if students are not able to join a live session. 

You will also have access to tutor groups to support you throughout your studies. 

Teaching Fellows will support students at programme and module level, responding to student queries via discussion forums and as part of live teaching sessions, alongside the module leads. 

Induction and enrolment 

Online enrolment for Imperial College London typically opens at the beginning of September. If you have successfully met all of the conditions of your offer by this point, you will be able and asked to enrol online at this point. 

You will be inducted to the Coursera platform and have access to a specially designed induction course in advance of the start of the programme, and once you have successfully enrolled online with Imperial College London. This will allow you to familiarise yourself with the Coursera platform in advance of the start of the programme and set yourself up for success. 

The programme will start in the first week of October 2020 with an induction week, week commencing Monday 5th October 2020. 

The majority of your induction activity will be hosted online during this first week for you to meet us, your fellow students on the programme, of other programmes, and your tutors. These induction sessions will also be an opportunity for you to familiarise yourselves with the online platforms and tools we will be using throughout the year, and for all of us to set expectations around the programme and online/on campus learning and teaching. 

We are also looking to host an optional on-campus induction activity, for students who are able to join in person. Further details will be shared about this in due course. 

Throughout the year, we will continue with these opportunities to allow you to socialise and feel part of our the cohort. 

To this effect, a Global Disease Masterclass seminar series will run throughout the Autumn term and students will be able to join these added value sessions on-campus, if they are able to do so and capacity/space permitting (a booking system will be in place). The sessions will also be available for students to access online. This seminar series will not be compulsory for students to attend but provides access to and added value interaction as part of seminars/lectures from world-leading researchers within the fields of Public Health and Epidemiology. 

More information will follow regarding induction and enrolment as part of your Induction/Welcome pack later in the Summer. 

 

Programme structure and content 

The MSc Health Data Analytics and Machine Learning programme structure remains largely the same and as we planned to deliver. The full list of modules we will deliver are detailed here in the programme specification and structure diagram. 

As we do every year, we have enhanced and refined some of the modules we deliver, in response to student feedback. The changes compared to last year are as follows: 

Autumn term: 

· New core module ‘Molecular Epidemiology’: 

o The module aims to familiarise you with omics data including genomics, epigenomics, transcriptomics, proteomics and metabolomics that are commonly used in epidemiological studies. You will learn about the biological importance of each of the omics, the cutting-edge technologies that are used to assay them, challenges that arise in applying them to epidemiologic studies, and their inherent strengths and limitations. 

o It will provide a smooth introduction into OMICs sciences and will prepare you well for the ‘Computational Epidemiology’ module in the spring term. 

Spring term: 

· New core module ‘Population Health’: 

o The addition of a module in population health aims to complete the research picture, providing you with an understanding of research at a macroscopic/population level, which complements the individual level that is the main focus of computational epidemiology and molecular biology. 

o This module aims to familiarise students with some key topics in population health, as a pivotal research theme within the School of Public Health. The module will introduce some of the issues faced while analysing complex data sets with the aim of measuring the health of entire populations, and its environmental and social correlates and determinants. 

· New core ‘Health data research seminar series’: 

o The programme currently includes a series of research lectures and additional methodological lectures, but to ensure you do not miss out on the excellent opportunities to form academic connections, reinforce your methodological background, and gain an applied understanding of the kind of research projects that are ongoing in the field you are studying, we will be organizing a series of research talk illustrating how these approaches have been developed and used 

o They will form a mandatory core module with monitored attendance. 

o This module aims to give you an overview of the areas of active research that the programme is training you in. The objective is to draw clear links between the methods you are learning and the practical application of these methods, as well as giving you an understanding of how scientific research is conducted in this field. 

o This module consists of a series of keynote lectures, seminars and student-led journal clubs, inviting leading researchers in the fields of health data research, computational epidemiology and machine learning. 

Summer term: 

· Changes to ‘Research Project’ ECTS and time duration: 

o The research project is being reduced in ECTS credit size (from 45ECTS to 30ECTS) and timeline (from 6 months to 4 months) to bring it in line with other Master courses in the School, allowing more time for you to gain essential research and technical skills in the spring term 

o Assessment/word count has been amended in line with this reduction but it does not fundamentally change the projects nor the output. 

o You will still be exposed to novel and additional scientific concepts that are very relevant for Data analytics and broaden the field of application of such approaches 

o You will still experience in practice how to critically read/listen to scientific output and will be given the opportunity to interact with international researchers 

Assessments 

The College policy is that the default alternative arrangement for any on-campus formal written examinations is to provide a timed remote assessment. 

For other types of assessment, the method may be amended to accommodate the multi-mode arrangements. All students participating in a piece of assessment will do this in the same way. For the Autumn term 2020-21 all assessments will be completed in a remote format. Details of individual assessments will be provided in the Programme Handbook/Module handbooks at the start of term. 

Assessment submission and any time based assessments will be facilitated through our Virtual Learning Environment (Blackboard). 

Assessment methods include: 

  • Essays 
  • Reports and paper reviews 
  • MCQs and online quizzes 
  • Open book/timed exam assessments 
  • Mini research project 
  • Individual and group presentations 
  • Video blogs 
  • Articles and case study reviews 

Detailed assessment guidance and briefs will be provided to you per module. 

 

Additional costs/technical requirements 

This will require you to have access to a computer and a reliable internet/wifi signal for the term, as you will be required to engage with/access teaching and live sessions from where you are based globally, and you will need to cover any associated costs for these. There are no other expected additional costs (beyond those previously advertised) to participate in the programme if you choose to study remotely. Please find further information here about technical requirements and expectations to engage successfully with the programme. 

 

Student Experience 

Your experience at Imperial goes beyond just your academic studies. With the impact of coronavirus (COVID-19), Imperial has been working with your Union to ensure that we are able to provide, enhance and facilitate all areas of your student experience under all eventualities. We identified key pillars of the wider student experience: academic experience; research culture and environment; amenities and accommodation; student community; wellbeing support; co-curricular activities and extra-curricular activities. Information on how we will deliver these, along with information on our Library Services, considering current social distancing restrictions, as well as a full lockdown, are set out on our website.

How we can answer your questions As always, should you have any questions, please contact us via msc-health-data-sph@imperial.ac.uk and we will be delighted to help with anything that you might need further information about. 

If you would like to explore what will be available to you as an Imperial College London student when you join, you can read more here.

On this site you will find the latest guidance for applicants and offer holders. You can also discover how Imperial is combatting coronavirus.

Thank you for choosing the School of Public Health and Imperial College London as the institution to undertake your postgraduate studies. We are enthusiastic about you joining our outstanding student body, and look forward to welcoming you in the Autumn, online! 

Prof Deborah Ashby, Professor Paul Elliott and Dr Marc Chadeau-Hyam 

Director of School of Public Health & Programme Co-Directors 

MSc Health Data Analytics and Machine Learning