Data Visualization using R Programming.

Learn why, what, how about data visualization in simple and easy way by using R

Created by : Rated :4.8 69633 views

Last Updated: 2022-07-25 10:07:32 English Course Type: Self Learning

Data Visualization using R, Pie Charts, 3D Pie Charts & Bar Charts.
Box Plots.
Histograms & Line Graphs.
Scatter Plots & Scatterplot Matrices.
Low Level Plotting.
Bar Plot & Density Plot.
Combining Plots.
Analysis with ScatterPlot, BoxPlot, Histograms, Pie Charts & Basic Plot.
MatPlot, ECDF & BoxPlot with IRIS Dataset.
Additional BoxPlot Style Parameters.

If you want to work in exciting analytics and data visualization project, then this is the starting point for you.
Data is the currency of now and potential to use it the right way, at the right time for the right reason gives you possibility beyond imagination.
Data visualization is a vast topic and consist of many sub-parts which are a subject in itself, we in our course have tried to paint a clear picture of what you need to know and what people will be looking of you in a visualization project.
UX in Data visualization is key in modern times to meet the expectation of your user, this course will highlight what are the benefits of using a good UX and how to do it.
This course is structured to provide all the key aspect of Data visualization in most simple and clear fashion.So you can start the journey in Data visualization world.

Having a basic understanding about statistics.

Beginner Python developers curious about Data Science.

Section 1 : Introduction. 1 Lectures 00:01:34
Lecture 1 :
Introduction Preview
Section 2 : Data Visualization using R, Pie Charts, 3D Pie Charts & Bar Charts. 1 Lectures 00:59:20
Lecture 1 :
Data Visualization using R, Pie Charts, 3D Pie Charts & Bar Charts.
Section 3 : Box Plots. 1 Lectures 00:54:38
Lecture 1 :
Box Plots.
Section 4 : Histograms & Line Graphs. 1 Lectures 00:45:26
Lecture 1 :
Histograms & Line Graphs.
Section 5 : Scatter Plots & Scatterplot Matrices. 1 Lectures 01:03:47
Lecture 1 :
Scatter Plots & Scatterplot Matrices.
Section 6 : Low Level Plotting. 1 Lectures 00:56:01
Lecture 1 :
Low Level Plotting.
Section 7 : Bar Plot & Density Plot. 1 Lectures 00:46:31
Lecture 1 :
Bar Plot & Density Plot.
Section 8 : Combining Plots. 1 Lectures 00:35:37
Lecture 1 :
Combining Plots.
Section 9 : Analysis with ScatterPlot, BoxPlot, Histograms, Pie Charts & Basic Plot. 1 Lectures 00:51:07
Lecture 1 :
Analysis with ScatterPlot, BoxPlot, Histograms, Pie Charts & Basic Plot.
Section 10 : MatPlot, ECDF & BoxPlot with IRIS Dataset. 1 Lectures 01:02:55
Lecture 1 :
MatPlot, ECDF & BoxPlot with IRIS Dataset.
Section 11 : Additional BoxPlot Style Parameters. 1 Lectures 01:01:41
Lecture 1 :
Additional BoxPlot Style Parameters.
Section 12 : What is Data Science. 1 Lectures 00:30:42
Lecture 1 :
What is Data Science.
Section 13 : What is Machine Learning. 1 Lectures 00:25:06
Lecture 1 :
What is Machine Learning.
Section 14 : Data Visualization using Pandas. 1 Lectures 00:19:33
Lecture 1 :
Data Visualization using Pandas.

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Datahill Solutions,

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Having 10+ Years of Experience in Software Industry which includes Development, Support & Training. My Experience Includes Managing, Processing, Predicting and Analyzing of Large volume of Business Data. Expertise in Data Management, BI Technologies & Data Science with Data Analytics, Machine Learning, Deep Learning & Artificial Intelligence using R Programming, Python Programming, WEKA and EXCEL. Having publications and patents in various fields such as machine learning, data security, and data science technologies. I received my Masters of Technology in Computer Science & Engineering from JNTU. Professionally, I am a Data Science management consultant with over 8 years of experience in finance, retail, transport and other industries.