Analyze Features with Python and Seaborn in Google Colab

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Last updated on April 21, 2025 12:44 pm

Boost your career in data science with this comprehensive Python training course. Learn statistical modeling, data visualization, and machine learning techniques to gain a competitive edge in the age of big data.

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What you’ll learn

  • Learn how to work with different types of data
  • Calculate the measures of central tendency, asymmetry, and variability
  • Distinguish and work with different types of distributions
  • Perform hypothesis testing

Complete Guide to Practical Data Science with Python: Learn Statistics, Visualization, Machine Learning & More

THIS IS A COMPLETE DATA SCIENCE TRAINING WITH PYTHON FOR DATA ANALYSIS:

It’s A Full 12-Hour Python Data Science BootCamp To Help You Learn Statistical Modelling, Data Visualization, Machine Learning & Basic Deep Learning In Python!

HERE IS WHY YOU SHOULD TAKE THIS COURSE:

First of all, this course a complete guide to practical data science using Python…

That means, this course covers ALL the aspects of practical data science and if you take this course alone, you can do away with taking other courses or buying books on Python-based data science.

In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal. By storing, filtering, managing, and manipulating data in Python, you can give your company a competitive edge & boost your career to the next level!

NO PRIOR PYTHON OR STATISTICS/MACHINE LEARNING KNOWLEDGE IS REQUIRED:

You’ll start by absorbing the most valuable Python Data Science basics and techniques…

I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in Python.

My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement Python-based data science in real life.

After taking this course, you’ll easily use packages like Numpy, Pandas, and Matplotlib to work with real data in Python.

You’ll even understand deep concepts like statistical modelling in Python’s Statsmodels package and the difference between statistics and machine learning (including hands-on techniques).

I will even introduce you to deep learning and neural networks using the powerful H2o framework!

Who this course is for:

  • People who want a career in Data Science
  • People who want a career in Business Intelligence
  • Business analysts
  • Business executives

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    Analyze Features with Python and Seaborn in Google Colab
    Analyze Features with Python and Seaborn in Google Colab
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