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Python Data Science

Learn Python in a Week and Master It. An Hands-On Introduction to Big Data Analysis and Mining, a Project-Based Guide with Practical Exercises: 7 Days Crash Course, Book 3

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Python Data Science

Auteur(s): Computer Programming Academy
Narrateur(s): Jeff Bower
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À propos de cet audio

Would you like to learn to use Python extracting meaningful insight from data to grow your business but you reckon it will be too complex? Or perhaps you want to know how to analyze data to solve simple domestic issues but you don’t know how to do it?

Here's the deal. As a beginner, you will be probably afraid that programming is difficult. Learning data analysis and data mining can take months, and the possibility to give up before mastering them could be high.

The best solution is a complete programming manual with hands-on projects and practical exercises. Computer Programming Academy structured this guide as a course with seven chapters for seven days and studied special exercises to apply what you learned step-by-step.

In the detail, you will learn:

  • The importance of data science technologies in our daily lives
  • What are the most common mistakes to avoid when you start dealing with Python for data science
  • Three important actions required to gain insights from big data
  • What are the advantages of the data mining process in resolving real world problems
  • How to download and use the main Python based data analysis libraries
  • The method to implement predictive analytics to resolve a business issue in less than seven days
  • A proven strategy to develop predictive models to analyze customers’ behavior
  • Exercises and quizzes at the end of every chapter to review immediately what you’ve learned

This is what this guide offers to you...even if you're completely new to programming in 2020 or you are looking to widen your skills as programmer.

The key to become a Python master is one click away!

©2020 Computer Programming Academy (P)2020 Computer Programming Academy
Programmation et développement de logiciels Apprentissage automatique Science des données Programmation Entreprise Exercice physique Intelligence artificielle Exploitation minière
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