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Avis et commentaires pour d'étudiants pour Exploration analytique de données par Université Johns-Hopkins

4.7
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5,744 évaluations
830 avis

À propos du cours

This course covers the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data. We will cover in detail the plotting systems in R as well as some of the basic principles of constructing data graphics. We will also cover some of the common multivariate statistical techniques used to visualize high-dimensional data....

Meilleurs avis

Y
23 sept. 2017

Very good course! It provide me the foundation in learning how to plot and interpret data. This will definitely strengthen my "R programming" to generate publication type figure for my genomics data!

CC
28 juil. 2016

This is the second course I have taken from Roger Peng and both were outstanding. I have a strong math background, but not much of a background in stats, but this course was very approachable for me.

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76 - 100 sur 799 Avis pour Exploration analytique de données

par Yudhanjaya W

6 juin 2017

This was incredibly useful because it gives you a feel for the datasets and tools with which to explore them. I really wasn't aware of the base and lattice plotting systems until now.

par Nino P

24 mai 2019

Amazing! Learing so much how to explore the data for the first time. This is a must do for anyone who wants to be a data scientist. Now I can use ggplot without any trouble. Thanks!

par VÍCTOR M G P

28 sept. 2020

Me encantó el curso, fue muy fluido con muy buenos ejemplos y las actividades prácticas fueron realmente un aporte y un desafío para complementar los contenidos entregados

par Manuel A A T

27 mars 2016

This is a great introductory course on the topic and on R language.

You will get acquainted with basic R functions which are most useful for initial statistical analysis.

par Vasco A F R B P

5 avr. 2020

One of the most fulfilling courses I've taken. Already used what I've learned to analyse the COVID 19 data and get more information from it, learning at the same time.

par Sanjay L

22 mai 2018

Week 3 - clustering concepts appear hard to comprehend initially. This week should first start with a practical example/use of clustering and then move on to technical

par Asif M A

4 mai 2016

Its one of the most important steps in learning data science. Before even jumping into the real thing, it is worthwhile to explore a little bit the data set at hand.

par Tim S

18 avr. 2016

For someone new to data analytics, this was another great, rewarding course. But as with the others, it demands exploration beyond the lectures and course materials.

par Giovanna A G

15 oct. 2016

Prof. Peng teaches you not only how to use the r base plotting system but also how to make wonderful graphs using the lattice and ggplot2 packages. Awesome course!

par Rob S

21 janv. 2020

Very good resume of the previous lessons, you lear plotting, charts, working with big matrices, create a good practical workflow to understand your first analyses

par Piotr K

23 oct. 2016

Material teached in this course is must have for everybody who wants to use R for Data Science. Exploratory Data Analysis is one of first steps in every project.

par Araks S

20 juin 2017

Great course, an excellent instructor who makes the videos easy to watch and listen.

Assignments were very important to me, as I learned a lot while doing it.

par Gary T

20 août 2019

I learned a lot, this course more than others, really expanded my competence and appreciate for the capabilities of R, especially is visualization toolbox.

par Jeffrey G

6 juil. 2017

Great course. Really does a good job of describing the goal of EDA and getting people excited about what questions you might be able to answer with data.

par 王昊辰

11 déc. 2018

The data used for training are too big to be processed on my computer....

It is a real burden for my laptop when I use Rstudio to view some big files.....

par Dmytro K

3 févr. 2016

pretty good starter course. I liked 40 min Case Study video at the end. It was very helpful to watch the instructor do the analysis from start to finish.

par Deleted A

23 juil. 2018

Excellent course!

Congratulations and thanks to the teachers of this course for sharing their knowledge on such an engaging subject that is Data Science.

par David J G

3 févr. 2016

I think this is a great course. I learned a lot about data plotting and some multivariate techniques for understanding underlaying patterns of the data.

par Sandeepkumar P

1 févr. 2016

Wonderful course with lot of graphical representation of the data. Dimensional reduction and Clustering analysis needs a bit more detailed explanation.

par Nathan D

18 oct. 2016

Very solid class in terms of R's base plotting system. I wish Coursera offered an advanced class focusing on ggplot2 and the wider world of dat viz.

par Alfredo A

6 févr. 2018

This was a great course. I learned how to use several graphic systems within R, and to imagine how to make clear answers to questions using plots.

par Athanasios S

16 juil. 2018

Very good class. Of the four I've taken so far, this one has given me the most confidence that I could be successful as a data scientist/analyst.

par Alexis C

11 août 2017

This was an important class because in future classes in the certification peer reviewed projects require some sort of exploratory data analysis.

par David S

22 avr. 2019

Great Course. Lectures did diverge from Quizes and projects but still was good practice of looking at a set of data and reporting out from it.

par Fenneken K

7 févr. 2020

Learned a great deal. Especially on clustering.

The second project could be a little more challenging; I overestimated the answers requested.