I think it is appropriate that the knowledge level required for this course is "intermediate". If you are a novice R programmer like I am, you will need to grow your R knowledge.

If your knowledge of differential equations is rusty, like mine, do not despair. If you've never taken a class in differential equations or calculus--you will need to understand the equations at an intuitive level. Understand that differential equations express change in quantities over time and their solutions are the values themselves over time.. Learning the required inputs to deSolve and understanding its outputs is absolutely critical to success in this course.

I had a lot of issues with the Jupyter pages. I never figured out how to copy and paste R code to the Jypyter cells or from previous pages as was suggested in Week 3.

I had some background in epidemic models from another Coursera MOOC using spreadsheets and difference equations. I learned a great deal of additional material from this course. I think the instructors were superb communicators and the material was well thought out.

I am glad I took the course.

Excellent primer for SIR models. I had no background in this field but enjoyed the course. A good working knowledge of R will be helpfpul.

I've made so much progress in the few days since I started the course! My main objective has been totally met: I can see where the epidemic projection curves that we're shown by the authorities come from and I have now a flavour of how the modelling process works, what the parameters that drive its dynamics are, and have an intuitive feel for what public health interventions might affect them. And I've managed to explain the models and how the curves move to family who are laymen in epidemiology - and they got it! Apart from that, I've brushed my rusty differential calculus and I've used R for the first time (was more of an Octave person). So my expectations have been exceeded. I thank Imperial and the Professors who put together the course for having provided a pleasant and very rewarding learning experience.

This was excellent. The course content was challenging enough to feel worth the time, but not so technical that it was a barrier. As well as the basics of mathematical modeling of infectious disease epidemics, the course also includes some generic skills around logical thinking and R programming. In particular, the accessible introduction to solving systems of differential equations in R feels like a really valuable skill. The lectures were short but covered the necessary content. There wasn't too much reading (if anything, I could have done with a little more reading, and one of the readings felt a bit too technical compare to the level of the course).

I really enjoyed this course. The theory and programming of the SIR model was taught very clearly. Even though I don't have a mathematical background I was able to understand all the content. This course also included some quite challenging programming exercises that really allows you to understand and experiment with the code yourself, which I thought was particularly useful. The course was also very manageble and I was easily able to complete it within the 4 weeks. I would recommend this course!

A very good course. The right balance between epidemiology knowledge and developer skills. Video lessons were short and lucid. R orientation and notebooks were great.

THis course introduces us to the very basics of epidemiological modeling but builds a solid foundation from which to build models in the real world

One of the best courses I have taken in Coursera! Would be better if you have a good working knowledge of R.Instructors are really good.

Interesting, easy to follow, and understand. I highly recommend to those interested in epidemiology and mathematically modeling.

Great learning !!

The structure and flow in the notebooks were somewhat disordered; the questions were some ambiguous, perhaps a revision in sentences required? Would be more helpful if the questions are unambiguous.

Today feeling more confident in CODING SIMPLE extensions to the basic SIR Model. Here I learnt three extension of SIR Model; Population Turnover, Vaccination and Waning Immunity. The unifying THREAD running through all of these different themes is that they are different modifies , so susceptibility in the EPIDEMIC....Susceptibility is just like the FUEL for an INFECTIOUS disease......

Vaccination is a way of removing the susceptibility's fuel by protecting people from infection without having to go through the disease state. So, policy makers need to DECIDE how often we vaccinate with what KINDS of does makes QUANTITIES... Thank you for every things, look forward to registered for another course...

If anyone want to learn about infectious disease modeling from scratch, using R programming language, This is the best course ever. This course will teach anyone not only the very basic, but will made everyone self sufficient to make and code their own model. You will not get any more clear and concise guidance and instruction anywhere. This course is worth of every bit of your payment and more than that. And it teaches all the practical aspects of modelling, that you can implement in real life.

This is a great course for an introduction to SIR modeling. The instructors are very clear in explaining concepts, and I enjoyed the R notebooks. The notebooks were pertinent to the course material, and it was nice use code built up from previous notebooks instead of always having a skeleton provided. One thing that would be a nice addition would be course slides to go with the videos.

In the Development of the SIR model; the Diseases that have a Substantial Asymptomatic phase are harder to CONTROL. One way of calculating this is dividing the number in each compartment by the total initial population size. The SIR model could be REPLICATED; however the Immunity is not Permanent, thanks for your excellent Training....look forward for future enduvarences....

SIR is simple fundamental but very powerful model. It starts with simple states of infectious disease and can develop in many way. Required just foundation of R programming. You should learn this SIR model and it'll become your powerful weapon to fight this Pandemic.

This whole specialisation is probably one of the best on Coursera. For me, it's been a wonderful experience from start to finish. The labs are well-prepared, the instructors are wonderful, and the discussion forum staff are incredibly helpful!

The course is quite excellent and it really helped me a lot in the developing of SIR as a model ,hence I do acknowledge the producer of this department since it boasted us whom are interested in modelling. Keep the standards up .

Very informative course! The instructors provided us the relevant well calibrated content. The etivities were designed to help us familiarize with the material and insight us to understand & solve problems ourselves.

The topic is very interesting and the exercises are good for fixing the knowledge. Difficulty is on point: not easy as to lose focus, but not too hard as to make us want to drop from it. 5/5!

This is an excellent course. It covers a lot of material, but is very well organized. Gives a great introduction to infectious disease modeling that is intuitive and easy to follow.

Nice course, good balance of videos and independent work. I have a question! What coding language is used in the etivities? Please help - no replies on the forums sadly! Thanks

This is the first coursera course I have done, excellent materials and clear explanations from the lecturers. I can't wait to have a look at the next part of the course!

It was a very informative course. I started with zero background in modeling. Now, I can understand the essential and fundamental aspects of modeling. Thank you!

This course lived up exactly to my expectations and more. I love their attention to detail and the fact that you are actively engaged in the learning process.