Ratings and Reviews for Fitting Statistical Models to Data with Python

Very Informative course. Learnt a lot statistical model fitting skills

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.

Nice as an introductory course

great course overall

good course

Week 3 and 4. Really painful. truly...truly...painful..

Very good courses and passionate teachers.

Like the other courses in this specialization, way too much theory covered, and the easy quizzes and labs give the learner a false confidence that he/she's mastering statistics. Instead, you grasp some of the theoretical knowledge, but not of the underlying math and therefore none of the intuition. The same is true of Python, all that's required is to hit the run cell button, no actual coding is required. The lecturers are super enthusiastic though, and the final week was fantastic. Mark Kurzeja should have his own course on probability and Bayesian statistics. Week 3 of every course has been super dense, and I think T Brady West should have his own course on sample design and weights because right now his lecturers drag down the overall quality of the course. It's all slides and text, math is brushed over and not enough of it is applied. Honestly, if you wanted to really get into Multilevel & Marginal Models you'd need 4 weeks. My advice, take the AP statistics course on Khan academy, watch some STATSQUEST on youtube & perhaps take the intro to statistics offered by Stanford University. You can also take this course/specialization and just skip weeks 3. You can probably pass the tests anyway Here's my rating by week. Week 1: 4* Week 2: 4* Week 3: 1* Week 4: 5*

I found the course to be good. I don't think it is excellent. Lectures can be a bit too long take some time to get to the point. Instructors are "ok", a lot of talking on most of them not enough math examples. Labs are pretty good but... I guess I can say that there are 5 star courses on this platform and this is not one of them. Its a solid 4. Still recommended.

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!