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    Back to Building on the SIR Model

    Learner Reviews & Feedback for Building on the SIR Model by Imperial College London

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    4.7
    stars
    23 ratings

    About the Course

    The other two courses in this specialisation require you to perform deterministic modelling - in other words, the epidemic outcome is
    predictable as all parameters are fully known. However, this course delves into the many cases – especially in the early stages of an epidemic –
    where chance events can be influential in the future of an epidemic. So, you'll be introduced to some examples of such ‘stochasticity’, as well
    as simple approaches to modelling these epidemics using R. You will examine how to model infections for which such ‘population structure’
    plays an important role in the transmission dynamics, and will learn some of the basic approaches to modelling vector-borne ...
    ...

    Top reviews

    GC

    Jun 24, 2020

    Filled StarFilled StarFilled StarFilled StarFilled Star

    I thought it was clear, the syntax problems were about the same topic and needed the solution talked about in the videos. The subject was completely covered. I already recommended it to like 5 people.

    IH

    Sep 21, 2020

    Filled StarFilled StarFilled StarFilled StarFilled Star

    A great learning opportunity. Advanced content presented in a convincing and understandable manner. Simply amazing.

    Filter by:

    1 - 13 of 13 Reviews for Building on the SIR Model

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Indunil M H

    •

    Sep 21, 2020

    A great learning opportunity. Advanced content presented in a convincing and understandable manner. Simply amazing.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By DHARMENDRA C K

    •

    Sep 20, 2020

    The importance of the SIR model is needs of an hour, due to COVID-19, HIV, Dengue, Hay-fewer and many more infectious diseases, in analysis and building of the Compartment model in which S-I-R; it stands for the Symptomatic-Infected-Recovered, When we need to build this model for our own country, we need to observed the PEAK prevalence (i.e. maximum number of symptomatic people during the epidemic), need to be considered, studied and analyzed. This course found to be helpful in order develop and build combination of paper-based and computer-based modelling, with the parameters their estimated values like R0 which is basic reproduction number, and so on.....thanks

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Rajendra A

    •

    Jun 28, 2020

    I have learnt a lot about infectious diesease modelling using SIR model, different modelling approach, its parameters/factors involved in the entire course/specialisation. All three courses in the specialization are really thoughtful for learners to progress further. Thanks to all mentors, discussion prompts, and co-learners on the discussion forum for the support. Special thanks to Imeprial College of London - Dr. Nim, Dr, Halder, Dr. Bowman and Ms. Nora Schmit for coming up with such a good course on Coursera platform.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Adeeb N

    •

    Jul 25, 2020

    This course was both educational and entertaining. The quality of the peer grading assignments was impressive (both in terms of getting tested and the quality of the work I got to review). Thoroughly recommend this course (and the entire specialization, really) to anyone with interest in infectious disease epidemiology in general. Kudos to the Imperial College team for this excellent set of courses.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By gabriel a c

    •

    Jun 24, 2020

    I thought it was clear, the syntax problems were about the same topic and needed the solution talked about in the videos. The subject was completely covered. I already recommended it to like 5 people.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Rajarshi B

    •

    Jul 29, 2023

    This course is really amazing .Excellent insight learning and gives room for nurturing the knowledge gained.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Amarnath T

    •

    Aug 14, 2020

    I have found it useful for increasing my insights into infectious disease modelling.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By kk m

    •

    Jul 2, 2023

    The peer review grade is not working properly. It is not showing result.

    Filled StarFilled StarFilled StarFilled StarFilled Star

    By Angelo A P L

    •

    Sep 7, 2020

    Excellent course, good information. Excellent instructors.

    Filled StarFilled StarFilled StarFilled StarStar

    By Nils K

    •

    Jun 10, 2020

    Overall one was given more variations on the SIR Model. While several models were talked about, I would have liked more info on the stochastic site. This course should be split up in two to go deeper into the modelling and maybe some other approaches than in R. Rating a paper in the end is good to give you basically the tools to model, but it should be also a bit deeper. But to get a quick overlook, it is definitely worthwhile.

    Filled StarFilled StarFilled StarFilled StarStar

    By David G

    •

    Jun 21, 2021

    a great follow up to the R coding course and a good entree into the world of public health

    Filled StarFilled StarFilled StarFilled StarStar

    By Debasish K

    •

    Jul 8, 2020

    Comprehensive. Notebooks were great

    Filled StarStarStarStarStar

    By MOHAMMED S Q

    •

    Jun 4, 2023

    the whole grading system is unfair

    … you have to wait for others to review

    your assignment which can take ages and may not happen at all

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