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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

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.

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!

필터링 기준:

탐구 데이터 분석의 844개 리뷰 중 26~50

교육 기관: omar k

2017년 10월 10일

limited and monotonous explanation

교육 기관: Dr. J P M

2020년 5월 2일

Not great course.

교육 기관: Johann R

2017년 5월 28일

Graphs and plotting is at the heart of data analysis and data science, and without it you would have difficulty conveying ideas, and having graphs to explain numerical/statistical data is always handy. Visual representation of a data set, and using visual cues to gain an understanding of data, can save a lot of time, and can help you gain additional insights into the data. This course teaches you key techniques on how to apply some graphing and plotting methods to visually explore data, and it does so really well and in great detail, and also provides some good demos.

교육 기관: Anthony C C

2017년 9월 27일

I was able to learn the material presented over the time of the course. It's a lot of material to cover in the time I could commit to it but I feel confident using the tools and methods presented. The projects were very valuable both from getting to practice the methods and tooling and also from seeing how other students approached the solutions. I really helped put all the options into context and highlighted the value of using the different tools and where to use them. Only knock would be sometimes the background noises in the videos were distracting.

교육 기관: Tarun S

2017년 4월 29일

I really appreciate the course design. Even if somebody doesn't have much background in R, she/he can comfortably learn from the videos and understand the concepts. The exercises and project assignments are challenging and actually help you practice and re-visit the lectures and explore further. Though I had already known and used Clustering, PCA and SVD in my work before, I really liked the way these concepts were explained here. I would strongly recommend this course to anybody who is keen to see R in action!

교육 기관: Amanuel G

2017년 1월 5일

It was a wonderful experience to read the structure of data before delving into the advanced statistical levels of data analysis.The need for inclusion or exclusion of dependent variables or dimension reduction in regression analysis can be intuitively understood and visualized using Data Exploratory techniques and then we have the clue as what to do in the next level.It is like putting the whole characteristic of the data under full control.

교육 기관: Monisha D

2020년 4월 23일

I strongly recommend this course to anyone who needs clearer understanding of data using Visualizations. The course is well structured and each lecture delivers new concepts in concise format with a very detailed swirl lessons to understand the working of each functions. At the end of the course, I got a completely different view of handling the data and how to extract maximum information from the data to gain meaningful insights.

교육 기관: Tejus M

2018년 5월 25일

This course is the first real step from using R for basic data manipulation/stats, to using it for advanced stats. However, the videos on PCA (principal component analysis) and SVD (singular value decomposition) were difficult to understand, and I had to view several videos on YouTube (e.g., StateQuest or Standord U) that do a far better job of explaining. Once I did that, the course videos seemed to make more sense.

교육 기관: José A R N

2016년 10월 20일

My name is Jose Antonio from Brazil. I am looking for a new Data Scientist career.

Please, take a look at my LinkedIn profile: https://www.linkedin.com/in/joseantonio11

I did this course to get new knowledge about Data Science and better understand the technology and your practical applications.

The course was excellent and the classes well taught by teachers.

Congratulations to Coursera team and Instructors.

교육 기관: Yusuf E

2018년 1월 5일

This course is nice but ggplot should have been given more emphasis probably. I really enjoyed the sections on SVD and PCA as these really require mathematical maturity. Other than that solid introduction to the plotting systems in R which is a must have. This course coupled with Applied Charting with Python will complete my skillset. Looking forward to the rest of the specialization.

교육 기관: Marcelo S

2017년 12월 11일

Great Course. Week 3 requires a bit of mathematical savvy (google SVD/PCA), but since there is no quiz, it won't affect your ability to finish the course, just your ability to fully understand what you are doing. The last project was a bit challenging, which is always good, but most of the information to complete it and earn full marks is in the discussion forums as usual.

교육 기관: Rimi Z

2018년 6월 22일

A great course I had to do research on the side to get some ideas and concepts that were presented in this course.... if this was my first course i would have found that not a good thing . However, every time i search i get better as a data science student and i know what to search for and how to find it and i think this is essential if you want to be a data scientist :)

교육 기관: Nguyen N H

2021년 5월 10일

This is a great course from Johns Hopkins University. I learn a lot through this course, from creating better color palettes to clustering data. The last project is interesting, in which I have to apply my R programming skills, data visualizations, and explore some other features in ggplot2 to solve the questions. Thank you Coursera and John Hopkins University.

교육 기관: Jorge E M O

2016년 7월 21일

A very good introduction to the exploratory analysis and the R's plotting systems. The most advanced exploratory techniques (singular values decomposition, etc.) are not explained in depth but the overall role that these kinds of statistical learning techniques plays in the exploratory analysis is firmly established.

Great work with the course!

교육 기관: Nelson S S

2020년 12월 21일

Gracias a la Universidad de Johns Hopkins y a los profesores Roger D. Peng PhD,

Jeff Leek, PhD, Brian Caffo, PhD por la generosidad en compartir su conocimiento.

Apreciados estudiantes, Mantenganse activos, mantenganse vigentes y motivados por su aprendizaje

Gracias Coursera por esa gran labor con la humanidad

교육 기관: Anirudh J

2017년 7월 6일

Dr R D Peng is clear, concise and teaches quite systematically so that data visualization and exploration is broken down into its constituent pieces and explained in a way I am yet to come across elsewhere in other MOOCs on the subject. I'm really impressed and happy to have taken up this course.

교육 기관: Arindam M

2017년 1월 5일

A great course. I was hoping to get some more hands on the actual case study though. It was mentioned that Exploratory Analysis is some times intertwined with modeling - and I think in later course it might get covered. But just a glimpse of the relation in the case study would have been helpful.

교육 기관: Cristóbal A

2016년 5월 17일

Material de muy buena calidad y a pesar que en ocasiones solo cumple un rol introductorio, el curso no deja de lograr con una simpleza reveladora la construcción de una base solida que luego sirve para profundizar en las herramientas presentadas.

Recomendado 100% y acorde a lo que propone.

교육 기관: Savitri

2018년 9월 10일

Best course to move in the field of Data Science and those who are starting on this field to move towards data science and Machine Learning this is gone help them so much. As the assignment part and the lectures are guided to you this gonna make you feel like best to have this course.

교육 기관: Roberto D

2016년 11월 21일

This class gave me insight on how to better analyze questions. My faults arose when trying to present to much information which may have caused confusion or even disinterest. The main point is to convey results in a simple and understandable manner. Good class lots of practice.

교육 기관: João F

2017년 11월 21일

Excelent course! I learned to make plots with the base plotting system and with the lattice and ggplot2 packages. Challenging assignments. It was great to learn about clustering, dimensionality reduction, SVD and PCA since they play a very important role in Data Science.

교육 기관: Travis M

2016년 1월 25일

A worthwhile course that breaks down methods for doing initial data analysis to get a rough feel of the data. It provides enough useful information about the 3 plotting systems in R and how they differ to allow the student to do sufficient exploration on his or her own.

교육 기관: Daniel C J

2016년 8월 12일

Loved the course! Super useful tutorial of the different plotting systems, and basic exploratory data analysis. Very practical and hands-on, which is what is needed for this kind of work. Assignments were relatively simple, but I think they got the key points across.

교육 기관: Jeff A

2018년 7월 24일

Great hands on course that will help me with a problem I needed to solve at work today. I’m very excited to start getting into the more real data analysis stuff. All the foundation work in this certificate is awesome and necessary but now the real fun is beginning

교육 기관: Tad S

2016년 2월 1일

If you know some R programming and want to learn how to generate plots for your data analysis, this course will give you a good start. I highly suggest doing swirl exercises after watching the lecture videos to reinforce your understanding of the course materials.