Data Visualization using Python and R.

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

Created by : Rated :4.6 68983 views

Last Updated: 2022-04-25 08:04:18 English Course Type: Self Learning

Learn and understand the importance of data visualization.
Learn about basic and advance chart types used in data visualization.
Get a solid understanding of how people work in data visualization project.
Learn what is user experience in data visualization and its importance.
Learn the psychology of visualization with Gestalt Principles.

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 mathematics.

People who want to get into data visualization.
Developers who want to work in analytics and visualization project.
Web, Mobile App and Software Designer.
Design thinker.
Graduate Students and University Students.

Section 1 : Introduction. 1 Lectures 00:01:25
Lecture 1 :
Introduction. Preview
Section 2 : Matplotlib Introduction. 1 Lectures 00:31:23
Lecture 1 :
Matplotlib Introduction.
Section 3 : PyPlot, Bar, Pie, Histogram, Scatter & 3D Plot. 1 Lectures 00:32:58
Lecture 1 :
PyPlot, Bar, Pie, Histogram, Scatter & 3D Plot.
Section 4 : Multiple Plots in a Graph. 1 Lectures 00:14:38
Lecture 1 :
Multiple Plots in a Graph.
Section 5 : Seaborn Plotting Functions. 1 Lectures 00:30:49
Lecture 1 :
Seaborn Plotting Functions.
Section 6 : Plotting with Categorical Data. 1 Lectures 00:15:40
Lecture 1 :
Plotting with Categorical Data.
Section 7 : Multi-Plot Grids. 1 Lectures 00:33:55
Lecture 1 :
Multi-Plot Grids.
Section 8 : Plot Aesthetics. 1 Lectures 00:17:39
Lecture 1 :
Plot Aesthetics.
Section 9 : 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 10 : Box Plots. 1 Lectures 00:54:38
Lecture 1 :
Box Plots.
Section 11 : Histograms & Line Graphs. 1 Lectures 00:45:26
Lecture 1 :
Histograms & Line Graphs.
Section 12 : Scatter Plots & Scatterplot Matrices. 1 Lectures 01:03:47
Lecture 1 :
Scatter Plots & Scatterplot Matrices.
Section 13 : Low Level Plotting. 1 Lectures 00:56:01
Lecture 1 :
Low Level Plotting.
Section 14 : Bar Plot & Density Plot. 1 Lectures 00:46:31
Lecture 1 :
Bar Plot & Density Plot.
Section 15 : Combining Plots. 1 Lectures 00:35:37
Lecture 1 :
Combining Plots.
Section 16 : 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 17 : MatPlot, ECDF & BoxPlot with IRIS Dataset. 1 Lectures 01:02:55
Lecture 1 :
MatPlot, ECDF & BoxPlot with IRIS Dataset.
Section 18 : Additional BoxPlot Style Parameters. 1 Lectures 01:01:41
Lecture 1 :
Additional BoxPlot Style Parameters.
Section 19 : What is Data Science. 1 Lectures 00:30:42
Lecture 1 :
What is Data Science.
Section 20 : What is Machine Learning. 1 Lectures 00:25:06
Lecture 1 :
What is Machine Learning.
Section 21 : Summary. 1 Lectures
Lecture 1 :
Summary.

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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.