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What you'll learn?
- 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.
Course Overview
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.
Pre-requisites
- Just some high school mathematics level.
Target Audience
- Beginner Python developers curious about Data Science.
Curriculum 11 Lectures 04:13:45
-
Section 1 : Introduction.
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Section 2 : Matplotlib Introduction.
- Lecture 1 :
- Matplotlib Introduction.
-
Section 3 : PyPlot, Bar, Pie, Histogram, Scatter & 3D Plot.
- Lecture 1 :
- PyPlot, Bar, Pie, Histogram, Scatter & 3D Plot.
-
Section 4 : Multiple Plots in a Graph.
- Lecture 1 :
- Multiple Plots in a Graph.
-
Section 5 : Seaborn Plotting Functions.
- Lecture 1 :
- Seaborn Plotting Functions.
-
Section 6 : Plotting with Categorical Data.
- Lecture 1 :
- Plotting with Categorical Data.
-
Section 7 : Multi-Plot Grids.
- Lecture 1 :
- Multi-Plot Grids.
-
Section 8 : Plot Aesthetics.
- Lecture 1 :
- Plot Aesthetics.
-
Section 9 : What is Data Science.
- Lecture 1 :
- What is Data Science.
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Section 10 : What is Machine Learning.
- Lecture 1 :
- What is Machine Learning.
-
Section 11 : Data Visualization using Pandas.
- Lecture 1 :
- Data Visualization using Pandas.
Our learners work at
Frequently Asked Questions
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Instructor
395436 Course Views
7 Courses
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.
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