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$29
  • Matplotlib Introduction.
  • PyPlot, Bar, Pie, Histogram, Scatter & 3D Plot.
  • Multiple Plots in a Graph.
  • Seaborn Plotting Functions.
  • Plotting with Categorical Data.
  • Multi-Plot Grids.
  • Plot Aesthetics.
  • What is Data Science.
  • What is Machine Learning.
  • Data Visualization using Pandas.

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.

  • Just some high school mathematics level.
  • Beginner Python developers curious about Data Science.
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  • Section 1 : Introduction. 1 Lectures 00:31:23

    • Lecture 1 :
  • Section 2 : Matplotlib Introduction. 1 Lectures 00:01:22

    • 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 : What is Data Science. 1 Lectures 00:30:42

    • Lecture 1 :
    • What is Data Science.
  • Section 10 : What is Machine Learning. 1 Lectures 00:25:06

    • Lecture 1 :
    • What is Machine Learning.
  • Section 11 : Data Visualization using Pandas. 1 Lectures 00:19:33

    • Lecture 1 :
    • Data Visualization using Pandas.
  • How do i access the course after purchase?

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    Yes absolutely & thats one of the advantage of self-paced courses. You can anytime pause or resume the course & come back & forth from one lecture to another lecture, play the videos mulitple times & so on.
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Datahill Solutions,

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.
View More...
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    Lecture 29
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    Tableau Server 2018 Administration

    By : Siddharth Pawar

    Lecture 26
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    Principles of Data Cleaning

    By : Phikolomzi Gugwana

    Lecture 25
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    Statistical Modeling for Data scien...

    By : Gulab Chand Tejwani

    Lecture 13
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    Data Preprocessing for Machine Lear...

    By : Dr. Nouman Azam

    Lecture 30
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