4.77 (117 reviews)
☑ Read In Data Into The R Environment From Different Sources
☑ Carry Out Basic Data Pre-processing & Wrangling In R Studio
☑ Learn to IDENTIFY Which Visualisations Should be Used in ANY given Situation
☑ Go From A Basic Level To Performing Some Of The MOST COMMON Data Preprocessing, Data Wrangling & Data Visualization Tasks In R
☑ How To Use Some Of The MOST IMPORTANT R Data Wrangling & Visualisation Packages Such As Dplyr and Ggplot2
☑ Build POWERFUL Visualisations and Graphs from REAL DATA
☑ Apply Data Visualization Concepts For PRACTICAL Data Analysis & Interpretation
☑ Gain PROFICIENCY In Data Preprocessing, Data Wrangling & Data Visualization In R By Putting Your Soon-To-Be-Acquired Knowledge Into IMMEDIATE Application
THIS IS YOUR ROADMAP TO LEARNING & BECOMING HIGHLY PROFICIENT IN DATA PREPROCESSING, DATA WRANGLING, & DATA VISUALIZATION IN R!
Hello, My name is Minerva Singh. I am an Oxford University MPhil graduate in Geography & Environment & I finished a PhD at Cambridge University in Tropical Ecology & Conservation.
I have +5 of experience in analyzing real-life data from different sources using statistical modelling and producing publications for international peer-reviewed journals. If you find statistics books & manuals too vague, expensive & not practical, then you’re going to love this course!
I created this course to take you by hand and teach you all the concepts, and tackle the most fundamental building block on practical data science - data wrangling and visualisation.
THIS COURSE WILL TEACH YOU ALL YOU NEED AND PUT YOUR KNOWLEDGE TO PRACTICE NOW!
This course is your sure-fire way of acquiring the knowledge and statistical data analysis wrangling and visualisation skills that I acquired from the rigorous training I received at 2 of the best universities in the world, the perusal of numerous books and publishing statistically rich papers in the renowned international journal like PLOS One.
HERE IS WHAT THIS COURSE WILL DO FOR YOU:
It will take you (even if you have no prior statistical modelling/analysis background) from a basic level of performing some of the most common data wrangling tasks in R.
It will equip you to use some of the most important R data wrangling and visualisation packages such as dplyr and ggplot2.
It will Introduce some of the most important data visualisation concepts to you in a practical manner such that you can apply these concepts for practical data analysis and interpretation.
You will also be able to decide which wrangling and visualisation techniques are best suited to answer your research questions and applicable to your data and interpret the results..
The course will mostly focus on helping you implement different techniques on real-life data such as Olympic and Nobel Prize winners
After each video, you will learn a new concept or technique which you may apply to your own projects immediately! Reinforce your knowledge through practical quizzes and assignments.
ON TOP OF THE COURSE, I’M ALSO OFFERING YOU:
Practice Activities To Reinforce Your Learning
My Continuous Support To Make Sure You Gain Complete Understanding & Proficiency
Access To Future Course Updates Free Of Charge
I’ll Even Go The Extra Mile & Cover Any Topics That Are Related To The Subject That You Need Help With (This is something you can’t get anywhere else).
& Access To A Community Of 25,000 Data Scientists (& growing) All Learning Together & Helping Each Other!
Now, go ahead & enrol in the course. I’m certain you’ll love it, but in case you don’t, you can always request a refund within 30 days. No hard feelings whatsoever. I look forward to seeing you inside!
Welcome To The Course
Introduction To The Course and Instructor
Data and Code Used in the Course
Install R and RStudio
Read in Data From Different Sources
Read in CSV and Excel Data
Read in Unzipped Folder
Read in Online CSV
Read in Googlesheets
Read in Data from Online HTML Tables-Part 1
Read in Data from Online HTML Tables-Part 2
Read Data from a Database
Common Data Pre-Processing Techniques
Basic Data Cleaning in R: Remove NA
Additional Data Cleaning
Indexing and Subsetting Data
Summarising Based on Qualitative Attributes
Of Long and Wide
Pre-processing Tasks and the Pipe Operator
Introduction to dplyr for Data Summarizing-Part 1
Introduction to dplyr for Data Summarizing-Part 2
Start with Tidyverse
Tidy Data: Long and Wide
Basic Data Visualization
What is Data Visualisation?
Some Principles of Data Visualisation
Exploratory Data Analysis (EDA) in R
More Exploratory Data Analysis with xda
Grammar of Graphics: ggplot2
Start with qplot
More qplot Visualizations
Start with ggplot
Scatterplots with ggplot2
Faceting With ggplot2
Insert a Smoothing Line
Barplots For Discrete Numerical Variables
Insert Error Bars
Additional ggplot2 Themes
Real Life Data Wrangling and Visualisation
Use dplyr and ggplot
What and How Can We Learn From Data?: Nobel Prize Winners
Mining More Information About Nobel Prizes
Mining and Visualising Information About the Olympic Games-Part 1
Of Winter and Summer Olympic Games
Of Men and Women
Work With R's Inbuilt Geospatial Data-Part 2
Use ggplot2 For Geographic Data Visualisations
This is an excellent course presented in a easy-to-learn way. Its practical application is significant and useful. overall An enriching experience .
The presenter is not clearly showing how she has set up Rstudio the way she has so it's very difficult to follow what exactly she's doing.
Its really a bad way to start a course when the data isn't organized. Some is on a master file, others is listed in lessons, and some is on github. There were missing files from the download and I had to go to the help board to see where its located. I don't know why the instructor didn't just take a few minutes of her time to spare the students many hours of theirs. Also, they do not answer questions. After 5 days of asking a question about a faulty file, they still had not responded. The instructor also makes mistakes by calling a data set a column, and visa versa, which is anathema for beginners. Stay away from this course. There are many other R (and Python) courses on udemy that are superior to this. They may not be called "Data Preprossessing" or "Data Wrangling" but they have these sections in their courses that actually make sense.
There was much useful information presented and I can adapt the code examples for my day to day activities.
This course is packed with great depth of content to learn about data wrangling and visualization techniques in R. It takes the learner through understanding what R has to offer then layers it with basic statistical concepts, since R is a statistical software. Next, it exposes the learner to applied techniques for analyzing data using R. To complete the learning experience, visualization techniques are shared that give a broad spectrum of knowledge about R packages for graphical output. Certainly a course worth a run through for anyone serious about learning R for data analysis. I was shy of giving 5 stars because the examples I found rather subdued. For example, different flower species, countries having gold medals were not exciting nor was the depiction of the roads and trails in Vietnam. Could lighten the denseness of the learning with data like chocolate consumption per capita, Netflix movie viewing by country, or countries having drone technologies or similar data examples to excite the learner.
Interesting learning experience and applicable to various job functions as well! Super high pedagogy, and She can really explain difficult concepts in an easy-going manner.
My experience was very positive but I would like to see more exercises because I understood the more complex elements.
Just awesome! Teacher is very knowledgeable and walks you through step by step. Excellent guidance on the installs.
Actually I did not have any idea how I should implement those information on to data visualization. it has definitely improved the quality of my visualisations.
Various concept are being covered and the course is well structured. I will surely recommend this course. I want the instructor to give more advanced studies on how we can connect Data Wrangling & Data Visualisation in R.
It is a very practical course in R. It will be good to include a section on visualizing geographic data
It's not a course I'd recommend, the instructor is not engaging, some key things from R functions are just "read" but not explained. Also, the instructor's explanation in some lectures and some questions in the Q&A are not satisfactory at all. This all would be ok if I was watching a free YouTube tutorial, but this is a paid course, and as such, not worth it
i think the presentation of this could be improved. for a starter, the clutter on the screen can be confusing.
Very hands-on and up to date course on R data wrangling. Like the in-depth treatment given to ggplot2. It will be good to have a section on interactive visualisation
I like the focus on the new wrangling packages. I think it would be good to have some geographic visualizations given that the instructor is an ecologist