LS
4.0Reviewed Oct 31, 2019
Good introduction. The swirl exercises kind of reproduce the lectures though- felt like it might not have been the most efficient use of time to go over the exact same example again.
Exploratory Data Analysis
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.
Status: Plot (Graphics)
Status: Dimensionality Reduction
Course56 hours
Featured reviews
YW
5.0Reviewed Jun 5, 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.
BB
4.0Reviewed Mar 8, 2017
When it comes to hierarchical and K-means clustering, the theory wasn't explained clearly. When do we use U and V for what purpose? How does D come in? I'm left confused after this.
CB
5.0Reviewed Jan 11, 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.
CB
4.0Reviewed Dec 10, 2016
The course is interesting and the content is relevant. I do think that there are some issues with project 2 though. I did provide feedback on that to the course administrators.
RS
4.0Reviewed Feb 13, 2017
Nice course, but too much focus on "R" as a tool.... Industries don't use R as much... The course must be made more generic and independent of R - understand it is not easy to do but ....
MB
5.0Reviewed Mar 28, 2022
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.
MS
5.0Reviewed Nov 25, 2020
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.
YF
5.0Reviewed Sep 23, 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!
MA
5.0Reviewed Jul 3, 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
TJ
4.0Reviewed Oct 17, 2018
Seems this would type of course in an online learning MOOC would be better if it was more direct hands on "how to" and less focused on explanatory fluff (academic style) .
NP
5.0Reviewed May 23, 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!