Thank you. End of course

[Marc_In_Singapore]

Almost finished the course! I still need to complete the wrap up quiz #7, a perfect way to be in sync with the on-going Tour de France 2021 and its mountainous stage 11 with Mont Ventoux.

Like many participants, I want to congratulate the pedagogical team and INRIA for putting such a high quality Machine Learning / Python / tabular data course. I have done quite a few MOOCs and in-person professional education courses but it is by far the most thorough and demanding course I have completed – the nights of the past seven weeks have not been easy! This course is equivalent to a university semester course, I think. One would hope that the team would put another course (e.g. non-tabular data, deep learning, etc.) but I have noticed that there is usually no “sequels” to a high quality course, as all the energies and enthusiasm of the team may have possibly gone into producing that first MOOC.

What you get from the course is commensurate with what you put in. From the results of the last two polling questions at the end of each quiz, I think I may have spent too much time on each lesson compared to other participants but it was well worth it (although, I would think that the completion time estimates are off by 30% - 50%; or maybe I am rusty, perhaps twice the average age of other participants, and for sure I was new to Python and its environment). I have preciously saved each notebook and, after another round of going through these notes, I may feel quite comfortable with all the course content and my ability to develop some relevant ML models.

Thanks again to INRIA for this great course.

[ArturoAmorQ]

Thanks a lot for the kind words! It is always great to get this kind of feed-back! We are still not sure if a sequel is coming soon but if that was the case, we would be really pleased to have you back.
And remember that learning has no age!

[lesteve]

@Marc_In_Singapore good one about the cycling wrap-up quiz and the Tour de France it almost looked like it was planned all along (it was not at all).

Congrats for finishing the MOOC and I will just add that it was a pleasure to interact with you on the forum!

[Marc_In_Singapore]

Wish list on the sequel: deep learning, GANs, text, image.

[ogrisel]

Thanks for the nice feedback!

The completion time estimates were completely guess work on our part for this first session. We will re-calibrated based on the average answers in the surveys of each module and sequence. This is why the surveys are so important for us.

[Luz_Mary]

Me uno para decir “Muchas gracias” a todo el equipo de INRIA, se que hay un gran trabajo detrás y a lo largo de todo el curso.
El nivel es muy bueno y aunque no lograré terminarlo en el tiempo establecido, seguiré desarrollando el curso a mi ritmo, hasta que lo tenga dominado.

Ojalá os animéis a proponer un próximo capítulo con los métodos más complejos!!

Y como siempre, desde Descartes hasta la fecha, un buen nivel académico y calidad humana de los franceses!!

[lesteve]

Ah là là c’est formidable les gens qui nous parlent dans leur langue, c’est la tour de Babel ce MOOC . La traduction en anglais:

I join to say “Thank you very much” to all the INRIA team, I know that there is a great work behind and throughout the course.
The level is very good and although I will not be able to finish it in the established time, I will continue to develop the course at my own pace, until I have mastered it.

I hope you will encourage me to propose a next chapter with more complex methods!

And as always, from Descartes to date, a good academic level and human quality of the French!!!

[Marc_In_Singapore]

A suggestion for those not knowing Python and its environment.

I have followed the Paris-Saclay course on statistics and R, where statistics is the focus and R the tool, and I found the R self-contained support documents / survival guides very useful; they can be short – see attached. Maybe such Python documents would be helpful to some, as it was challenging, but still rewarding, for me to Google StackExchange and other W3schools to find answers to beginner and non-beginner sometimes cryptic lines of code. That said, I did not check the provided Python references and maybe I should have.

Maybe I should also follow a Python course at some point.

Introduction à la statistique avec R

Paradis-rdebuts_fr.pdf

[ogrisel]

@Marc_In_Singapore

That said, I did not check the provided Python references and maybe I should have.

Maybe

[Eolindel]

I would like to add my cheers to the other ones expressed here : it is definitely THE best MOOC I followed.

The course was hard, but it confronted us to real exercices with common problems to deal. While the learning curve was steep, the course really helped to soften it while keeping high expectations.

We had few videos and it was good : they helped to explain some hard general concepts but are much slower than the jupyterhub handouts. I find the balance remarkable between all the different activities proposed (short questions, full exercises, optional exercices, videos, etc). It is so far from the typical dumb way of MOOCs with videos and then straightforward quizzes.

I second the others : please continue this great course with a new one about new topics : time series, deep learning, neural networks, supervised and unsupervised learning, images, etc.

I definitely sweat to pass the certification within the delays, but every trickle rose the feeling of true accomplishment. The real joy of learning was always there.

While some minor glitches where there, you were really responsive and your starting basis is a really great teaching material. As a university teacher, I’m truly impressed by how you managed to overcome the usual pitfalls of asynchronous learning.

[ogrisel]

Thanks for the very kind feedback!