Python For Data Science - Steve Tudor
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Présentation Python For Data Science de Steve Tudor Format Broché
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Résumé :
Do you want to master Data Science skills to prepare for a lucrative career while learning advanced concepts in Python Programming?
In our fast-paced world of today, data has become the new oil, and companies are finding new ways to use the insights provided by data to improve their bottom line and customer experience.
This has resulted in an explosion of demand for qualified data scientists that can make sense of vast amounts of data that will help companies make smart decisions.
If you want to discover a comprehensive guide that will help you get started using the power of Python to analyze data, create beautiful visualizations and master powerful machine learning algorithms, then this guide is for you.
In comprehensive guide is designed to provide a coding bootcamp experience at a fraction of the cost. In this guide, you're going to discover all the necessary skills you need to use Python to transform data into actionable insight.
Among the practical tips and techniques contained in Python Data Science, you're going to learn:What Data Science really is and why it's important in today's world
Real-world use cases of Data Science and Python and why the use of modern data analysis tools can transform your organization or business
5 data science tips and tricks that every data scientist should absolutely know about
How to get started collecting and analyzing data effectively with NumPy
The right packages to install in your Python that will make learning Python for Data Science a breeze
How to master array manipulation in Python
Practical workbook to help you practice your newfound skills with the Python language to perform basic data visualization
...and tons more!
Even if you're completely new to coding, you're are interested in Data Science or you've done some programming before and are looking to switch to an exciting new career track in Data Science, this guide will teach you all the basic techniques used by real-world data scientists and analysts to solve real-world problems.
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