This is the worst course I have ever wasted my time and patient on it. I don't understand how can a specialization with net materials including at most 30pages of pdf and 2 hours video get stretched for 12 weeks in lengthy boring videos mostly by young students who don't have a deep understanding of what they are talking about!! just to give you how pointless this specialization is I finished the 3rd course week 3 and 4 in 5 min by just solving quizes. this specialization explains ideas and materials which are so simple that you could grasp in 2 minute if explained by a knowledgable teacher, in hours on non sense boring repetitive shallow talks. no math explained properly, no plot explained properly. there are hours of videos that TAs going through notebooks and reading the code already written with no explanation of underlying mechanisms, which could shorten the specialization by removing them. I can't understand why this specialization is popular! maybe because you can get certificate without watching anything!

the focus only on statistics not python which I think is the main reason for every one who enrolled in this course, it was even too much fast for statistics and very poor python assessment and tutorials, I don't recommend this course to any one.

This was a poorly designed course compared to other online courses. A lot of different topics were covered without going into depth of any topic. Week 3 and Week 4 topics are not valuable at all.

Starting from week 3, the lecture becomes very confusing with a lot of unexplained terminologies. Very few examples were given to help understanding the concepts.

Desde mi punto de vista, considero que la especialización esta muy bien, sobre todo porque se refuerza de manera constante los aprendizajes teoricos, y al mismo tiempo existe la posibilidad de replicar el codigo dentro de los cuadernos de jupyter, ahora, evidentemente hay muchas cosas por mejorar, inicialmente el código ya esta depredado en muchos elementos y lo ideal sería corregir esto, también hay errores absurdos, por ejemplo dentro de los notebook hay errores y en muchas ocasiones no coincide el notebook con las explicaciones previas. En este ultimo curso, hubo un reto muy grande porque se explica que son los modelos de regresion lineal y logisticos, marginales y jerarquicos, y es un tema que desde mi punto de vista fue mucho más complejo de entender que los otros, entonces sería agradable que se incluyeran más ejemplos. No obstante, recomiendo enormemente esta especialización. Para mi tiene más cosas positivas que negativas, el foro es un mecanismo para salir de dudas y observar el avance de otros, además como ya lo mencione, creo que como aprendices necesitamos buenas bases conceptuales y esto nos ayudará a mejorar en proyectos propios o a entender otros cursos que tomemos con más facilidad.

This is a nice course that allows all your eugenic believes to be statistically justified! No, I'm kidding - I'm a medical professional and many topics in statistic courses touch medicine closely, and they're easy to interpret with malicious thought. This is obvious to me, but I doubt it is not non-medicals, including staff :) So, the real review: The course is excellent, easily the best of all three in the pack, and well worth studying. It is good that there is much more self-studying, and examples from the web are excellent. The previous two had some problems, but this one is top-notch. I recommend it highly!

Great statistical lessons, I did not realize there were more regression-type models besides Ordinary Least Squares, which expanded my learning horizon, and of course, applied using Python Jupyter Notebooks. Python Code was comprehensive and enabled easy following. It was immensely helpful as I did not know how to even begin constructing a linear model study, using independent or dependent data.

The most difficult course in this specification! The most important takeaway point of this course is to understand why we choose any model to fit our data, and how to interpret the model. Don't jump into complex math calculation, we got python to do that for us! Dr Brady did a very good job conveying those ideas to us.

p.s the forum has great discussion posts, make sure to use the forum.

I enjoyed it so much! Super didactical and easy to understand! Facilitators are amazing! Best quality videos and materials! I loved the Jupyter notebooks created by the content creators since I can use them later as examples when I work on my own research applications! Thank you, so much!

I have learnt to applying coding in statistical analysis. I really enjoyed the Week 4 Bayesian Statistics because the use of coding has added new favor to this topic. It makes the study a real science but not something set in the stone (textbook).

A great course on how to fit models to data. Very rich on theoretical concepts and equally great on the practical aspects of using python to fine-tune your model, viewing the same each time as you modify data. Very fine course indeed

I am very thankful to you sir.. i have learned so much great things through this course.

this course is very helpful for my career. i would like to learn more courses from you. thank you so much.

The course is actually pretty good, however the mix between basic subjects (like univariate linear regression) and relatively advanced topics (marginal models) may discourage some students.

This a fundamental course for everyone who is delving into data analytics. Important note: in order to access the full potential of the lectures, it is essential to attend all 3 courses!

Just like the other courses in the specialization, very well thought out and planned! Up to date, great professors . . . couldn't ask for more!

Great review of machine learning used in statistics finished up with some overview on bayesian math.

Enjoyed very much and learnt even more.

Excellent, the explanations were perfect and its theorical focus was the thing why I loved this course.

These whole three certifications lays the foundation for learning Machine Learning a more in-depth way.

The specialization covers important practical topics. I am glad to have the opportunity to explore it.

Overall really great coure that covers a lot of material in a concise way.

Excellent course! Thanks to the instructors and the team made this MOOC.

Very Informative course. Learnt a lot statistical model fitting skills

An excellent introductory course to the world of statistical modeling.

Excellent course, really enjoyed the section on Bayesian statistics.

Very informative and the example

applications are extremely detailed