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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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5,387 évaluations
778 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

CC

Jul 29, 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.

Y

Sep 24, 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!

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51 - 75 sur 749 Avis pour Exploration analytique de données

par Lloyd N

Dec 20, 2016

This course is excellent in that it gave a great introduction to the plotting functions in R. They also introduced singular value decomposition, which is a concept that is interested but wish the course went deeper into.

par BOUZENNOUNE Z E

Mar 10, 2018

That's a wonderful course, especially if you take it with the specialization, and also better if used with the recommended books. I highly recommend, but once you finish it, you should continue to work on your own ;)

par Garrett F

May 22, 2020

Learned how to look at data and get some first impressions using exploratory data analysis techniques. I wish the second course project was more involved by including hierarchical clustering methods in the analysis.

par Varun B

Mar 22, 2018

The right amount of theory and practical. This course will take you through the process on how do you ascertain what's important? and how to find that needle in the haystack? . Absolutely recommend to take this up.

par Runhao Z

Oct 17, 2017

The peer review takes so long..................................................................................... which costs me extra money even though I have finished all the stuff 1.5days before the last day.

par Rooholamin R

Feb 16, 2019

I learned a lot from this course. Content which the course covers was a third of what I learnt from this course. the best thing about it is learning the pattern of thinking about exploring a whole new dataset.

par James W

Sep 07, 2016

Really nicely explained, learned so many useful methods for data analysis in R. The dimensionr reduction and principal component analyses walkthroughs were a little tricky for a newbie in those areas though.

par Yang F (

Sep 24, 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!

par Craig

Jul 29, 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.

par Felix E

Jul 29, 2019

Good Course. Would've like a bit more about more advanced plotting and less about clustering techniques but that is probably mainly down to what data each is intending on handling after this course.

par Imran A

Jan 18, 2016

Very nice course, plotting data to explore and understand various features and their relationship is the key in any research domain, and this course teaches the skill required to achieve this.

par André V d C

Feb 02, 2016

Muito bom o curso com abordagem das formas de exploração dos dados via gráficos. Não achei um curso pesado e denso mas substancial para o aprimoramento na linguagem R e na ciência de dados.

par Eswara K

Jun 06, 2020

Awesome course that expands on your R knowledge. Only nitpick is that some of the links don't work and the videos need an overhaul as there seem to be little to no updates since 2015/2016.

par Mohammad A

Jul 04, 2018

Excellent explanation and adding very good skills on the way of data science specialization.For some slides they should be updated to have working URLs , some seems old and absolute now

par Mathew K

Dec 29, 2019

Great intro to plotting and related tools in R. Will say that the coverage of heatmaps and PCA felt a little out of left field, with very little intuition. However, overall quite good.

par Marco A I E

Aug 10, 2018

Loved it! It took me longer than expected due to work and family issues, but I went so many times to the materials and even use some ggplot2 for work that ended being quite fulfilling.

par Chris B

Jan 12, 2017

I did learn more about putting together a set of graphs that help to explore the data. I did see how subsetting and aggregating data helps to give a better understanding of the data.

par Leonardo M d O

Nov 07, 2017

Excellent course. I learned more than I expected. A technique that was always at hand but never used: perform analysis through graphics exploring countless variables at a single time.

par Yudhanjaya W

Jun 06, 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

May 24, 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 Manuel A A T

Mar 27, 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

Apr 05, 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

May 22, 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

May 04, 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

Apr 19, 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.