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탐구 데이터 분석(으)로 돌아가기

존스홉킨스대학교의 탐구 데이터 분석 학습자 리뷰 및 피드백

4.7
별점
5,981개의 평가

강좌 소개

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....

최상위 리뷰

Y

2017년 9월 23일

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

2016년 7월 28일

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.

필터링 기준:

탐구 데이터 분석의 844개 리뷰 중 76~100

교육 기관: Imran S

2020년 11월 26일

This is a great course. The basics are explained very clearly and very easy to understand. I highly recommend this course for those who wish to start in Data Analyst / Data Science track.

교육 기관: Mohammad A

2018년 7월 4일

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

교육 기관: Mathew K

2019년 12월 29일

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.

교육 기관: Marco I

2018년 8월 9일

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.

교육 기관: Chris B

2017년 1월 12일

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.

교육 기관: Leonardo M d O

2017년 11월 6일

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.

교육 기관: Yudhanjaya W

2017년 6월 6일

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.

교육 기관: Nino P

2019년 5월 24일

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!

교육 기관: Maulid B

2022년 3월 29일

The dimension reduction technique was so robust, typically, this course detailed the critical parts regarding the data pre-processing. It is pivotal for the downstream analysis.

교육 기관: Eduardo C

2021년 8월 5일

good course to get started on the topic of information exploration, as they say it is basic that we understand that to carry out an analysis we must first know the information.

교육 기관: VÍCTOR M G P

2020년 9월 28일

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

교육 기관: Manuel A A T

2016년 3월 27일

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.

교육 기관: Vasco A F R B P

2020년 4월 5일

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.

교육 기관: Sanjay L

2018년 5월 22일

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

교육 기관: Asif M A

2016년 5월 4일

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.

교육 기관: Tim S

2016년 4월 18일

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.

교육 기관: Giovanna A G

2016년 10월 15일

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!

교육 기관: Rob S

2020년 1월 21일

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

교육 기관: Piotr K

2016년 10월 23일

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.

교육 기관: Araks S

2017년 6월 20일

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.

교육 기관: Gary T

2019년 8월 20일

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

교육 기관: Jeffrey G

2017년 7월 6일

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.

교육 기관: 王昊辰

2018년 12월 11일

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.....

교육 기관: Dmytro K

2016년 2월 3일

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.

교육 기관: Deleted A

2018년 7월 23일

Excellent course!

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