- General welcome
Greetings and a warm welcome to LSHTM and the MSc Health Data Science programme!
From "Hello" to "Nǐ hǎo," we are thrilled to have you here.
Prepare to embark on a transformative journey that will shape you into a trailblazing health data scientist of the future. Our esteemed team of expert academics is eagerly awaiting your arrival, ready to provide unparalleled support, guidance, and mentorship as we embark on this adventure together.
Over the course of the academic year, you will witness a remarkable transformation as you advance your knowledge and skills. Our aim is to nurture and empower you to become a key player in the field of health data science, equipping you with the prowess to excel in both public and private sectors. Through a laser focus on developing strong quantitative, computational, and practical data management skills, complemented by opportunities to cultivate vital professional competencies, we aim to create a well-rounded and versatile health data scientist.
Once again, welcome to LSHTM and the MSc Health Data Science programme. Get ready to unleash your potential, seize opportunities, and make a lasting impact in the world of health data science.
Together, we will embark on an awe-inspiring journey of discovery, growth, and accomplishment. Rest assured, we are here for you every step of the way, providing unwavering support and guidance throughout the year.
If you have any questions, concerns or problems then please don’t hesitate to reach out to me at [email protected] and I will do all I can to help.
Stéphane Hué, Programme Director.
- Welcome Week
- Personal tutors
At the start of the programme you will be allocated a personal tutor with whom you will meet regularly throughout the year. Where possible we try to match personal tutors to the student’s background and areas of interest. To help us identify appropriate personal tutors for students, please complete our MSc Health Data Science student interest form by Friday 19th September 2025. The information in the form will be shared with your personal tutor.
- Preparing for the programme
Reading
You will be pleased to know we do not have a set reading list for this programme. As pre-course reading we recommend that you read and try examples in this Maths, Probablity and Statistics Refresher.
Computer
You will require a personal laptop computer to undertake the programme with either an up to date version of Windows or macOS.
- Information for new part-time students
Term 1
In the first year, part-time students are expected to attend the programme for 2.5 days per week. During this time you will complete the following modules: Thinking like a Health Data Scientist, Statistics for Health Data Science and Programming. In year 1 you are expected to be present for classes on Monday and Tuesday and the following sessions: Thursday 23rd October (Thinking like a Health Data Scientist), Wednesday 29th October (Thinking like a Health Data Scientist) and Thursday 30th October (Thinking like a Health Data Scientist).
In the second year, students will take classes on a Thursday and Friday. During this time you will complete Health Data Management and Concepts and Methods in Epidemiology.
Term 2
In term 2 of the first year you will complete the following modules: Machine Learning and Genomics for Health Data Science or another chosen option from Spatial Epidemiology in Public Health, Modelling and the Dynamics of Infectious Diseases, Analysis of Hierarchical and Other Dependent Data.
In the second year you will complete Data Challenge and the Analysis of Electronic Health Records or another chosen option from Environmental Epidemiology or Bayesian Statistics.
Summer research project
For part-time study you can split the project over two years or complete it in the second year. Please talk to the programme directors if you wish to complete the project in its entirety in year 2 as it requires 600 hours of learning time. In either case you will submit your project at the end of year 2.
- Health Data Science modules
In the table below you can see the compulsory and optional modules for the MSc Health Data Science. There are no optional modules in Term 1 and you will be required to select two optional modules in Term 2. We highly recommend you select the Genomics Health Data and Analysis of Electronic Health Records optional modules in Term 2 as we believe these will give essential skills needed in the Health Data Science field.
Term Compulsory modules Optional modules Term 1 (weeks 1-10) - Thinking like a Health Data Scientist
- Programming
- Health Data Management
- Concepts and Methods in Epidemiology
- Statistics for Health Data Science
N/A Christmas break Term 2 (weeks 11-20) - Machine Learning
- Data Challenge
Select one from:
- Genomics Health Data (Recommended)
- Modelling and the Dynamics of Infectious Diseases
- Analysis of Hierarchical and Other Dependent Data
- Spatial Epidemiology in Public Health
Select one from:
- Environmental Epidemiology
- Bayesian Statistics
- Analysis of Electronic Health Records (Recommended)
Easter break Term 3 - Summer project
N/A - Health Data Science module schedule
Term 1
In Term 1 there are four module slots called A1, A2, B1 and B2:
Slot When Period Length A1 Before Reading Week Mon (AM) to Wed (lunchtime) 5 weeks A2 Before Reading Week Wed (PM) to Fri (PM) 5 weeks B1 After Reading Week Mon (AM) to Wed (lunchtime) 5 weeks B2 After Reading Week Wed (PM) to Fri (PM) 5 weeks Term 1 timetable
Date Week Mon AM Mon PM Tue AM Tue PM Wed AM Wed PM Thu AM Thu PM Fri AM Fri PM 22-Sep 29-Sep 1 THDS Stats Prog Prog HDM HDM CME CME 6-Oct 2 THDS Stats Prog Prog HDM HDM CME CME 13-Oct 3 THDS Stats Prog Prog HDM HDM CME CME 20-Oct 4 Stats Stats Prog Prog THDS THDS CME CME 27-Oct 5 Stats Stats Prog Prog THDS THDS THDS THDS Reading week 10-Nov 6 THDS Stats Prog Prog HDM HDM CME CME 17-Nov 7 THDS THDS Prog Prog HDM HDM CME CME 24-Nov 8 Stats Stats Stats Stats HDM HDM CME CME 1-Dec 9 Stats Stats Stats Stats HDM HDM CME CME 8-Dec 10 Stats Stats Stats HDM HDM Key
THDS – Thinking like a Health Data Scientist
Stats - Statistics for Health Data Science
Prog - Programming
HDM - Health Data Management
CME – Concepts and Methods for Epidemiology
Blank - free self-directed study timeTerm 2
In Term 2 there are four module slots called C1, C2, D1 and D2:
Slot When Period Length C1 Before Reading Week Mon (AM) to Wed (lunchtime) 5 weeks C2 Before Reading Week Wed (PM) to Fri (PM) 5 weeks D1 After Reading Week Mon (AM) to Wed (lunchtime) 5 weeks D2 After Reading Week Wed (PM) to Fri (PM) 5 weeks Term 2 timetable
Date Week Mon AM Mon PM Tue AM Tue PM Wed AM Wed PM Thu AM Thu PM Fri AM Fri PM 12-Jan 1 ML ML ML ML Chall Chall Chall Chall Chall 19-Jan 2 ML ML ML ML Chall Chall Chall Chall Chall 26-Jan 3 ML ML ML ML Chall Chall Chall Chall Chall 2-Feb 4 ML ML ML ML Chall Chall Chall Chall Chall 9-Feb 5 ML ML ML ML ML Chall Chall Chall Chall Chall Reading week 23-Feb 6 Geno Geno Geno Geno EHR EHR EHR EHR EHR 2-Mar 7 Geno Geno Geno Geno EHR EHR EHR EHR 9-Mar 8 Geno Geno Geno Geno EHR EHR EHR EHR 16-Mar 9 Geno Geno Geno Geno EHR EHR EHR EHR 23-Mar 10 Geno Geno Geno Geno EHR EHR EHR EHR Key
ML - Machine Learning
Chall - Data Challenge
Geno - Genomics Health Data (or other option chosen)
EHR - Analysis of Electronic Health Records (or other option chosen)
Blank - free self-directed study time
- Summer research project
All students as part of the MSc will be required to undertake a project from April to August. Health Data Science projects usually involve the data management and analysis of real life data which could be electronic health records, clinical trials or epidemiological studies for example. Project focusing on improving data analytics via the design of apps or other software may be permitted.
Students should discuss summer project ideas with your personal tutors before Christmas 2025 and all projects will need a favourable opinion from the School Ethics committee before commencing in April.
Page last updated July 2025