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PYTHON: Learn Coding Programs with Python Programming and Master Data Analysis & Analytics, Data Science and Machine Learning with the Complete Crash Course for Beginners - 5 Books in 1
If yes, then this Python for Beginners Crash Course is for you. This is the most complete Python guide with 5 Manuscripts in 1
1-Python For Beginners
2-Python Advanced Programming
3-Python for Data Analysis & Analytics
4-Python for Data Science
5-Python Machine Learning
A great Simplicity, Best Order and Selection of topics to Learn Fast and Selected Practice Exercises and Examples.
In Manuscripts 1 and 2 “ Python For Beginners ” and “ Python Advanced Programming ” you'll
- What is Python
- How to install Python and what is the best distribution
- What are data types and variables
- How to work with numbers in Python
- What operators there are in Python and when to use them
- How to manipulate Strings
- How to implement Program Flow Controls
- How to implement loops in Python
- What are Python lists, Tuples, Sets, Dictionaries, and how to use them
- How to create modules and functions
- How to program according to the Object-Oriented paradigm
- How to create classes
- What are and how to use Inheritance, Polymorphism, Abstraction, and Encapsulation
And much more...
In Manuscript 3 “ Python for Data Analysis & Analytics ” you'll
- What Data Analysis is and why it is important
- What are the different types of Data Analysis
- What are the 6 key steps of the Data Analysis process that you should follow
- What are the applications of Data Analysis and Analytics
- How to set up the Python environment for Data Analysis
- What are and how to use Python Data Structures
- How to work with IPython/Jupyter Notebook
- How to work with NumPy
- How to visualize data with Matplotlib
- What other visualization libraries are out there
- Why is Big Data important and how to get the best out of it
- How to leverage Neural Networks for Data Analysis
And much more…
In Manuscript 4 “ Python for Data Science ” you'll
- What is Data Science and what does it encompass
- What are the 5 key steps of the Data Science process that you should follow
- How to set up the Python environment for Data Science
- How to work with Seaborn data visualization module
- What are the most important Machine Learning Algorithms
- How to leverage the Scikit-Learn module for Machine Learning
- How to leverage Data Science in the Cloud
- What are the most important applications of Data Science
And much more…
In Manuscript 5 “Python Machine Learning” you’ll learn
- What is Machine Learning and what does it encompass
- What are the 7 Steps of the Machine Learning Process
- What are the different Machine Learning types
- How is Machine Learning applied to the real world
- What are the main Data Mining techniques
- How to best set up the Python environment for Machine Learning
- What are the most important Python libraries for Machine Learning
And much more…
1-Python For Beginners
2-Python Advanced Programming
3-Python for Data Analysis & Analytics
4-Python for Data Science
5-Python Machine Learning
A great Simplicity, Best Order and Selection of topics to Learn Fast and Selected Practice Exercises and Examples.
In Manuscripts 1 and 2 “ Python For Beginners ” and “ Python Advanced Programming ” you'll
- What is Python
- How to install Python and what is the best distribution
- What are data types and variables
- How to work with numbers in Python
- What operators there are in Python and when to use them
- How to manipulate Strings
- How to implement Program Flow Controls
- How to implement loops in Python
- What are Python lists, Tuples, Sets, Dictionaries, and how to use them
- How to create modules and functions
- How to program according to the Object-Oriented paradigm
- How to create classes
- What are and how to use Inheritance, Polymorphism, Abstraction, and Encapsulation
And much more...
In Manuscript 3 “ Python for Data Analysis & Analytics ” you'll
- What Data Analysis is and why it is important
- What are the different types of Data Analysis
- What are the 6 key steps of the Data Analysis process that you should follow
- What are the applications of Data Analysis and Analytics
- How to set up the Python environment for Data Analysis
- What are and how to use Python Data Structures
- How to work with IPython/Jupyter Notebook
- How to work with NumPy
- How to visualize data with Matplotlib
- What other visualization libraries are out there
- Why is Big Data important and how to get the best out of it
- How to leverage Neural Networks for Data Analysis
And much more…
In Manuscript 4 “ Python for Data Science ” you'll
- What is Data Science and what does it encompass
- What are the 5 key steps of the Data Science process that you should follow
- How to set up the Python environment for Data Science
- How to work with Seaborn data visualization module
- What are the most important Machine Learning Algorithms
- How to leverage the Scikit-Learn module for Machine Learning
- How to leverage Data Science in the Cloud
- What are the most important applications of Data Science
And much more…
In Manuscript 5 “Python Machine Learning” you’ll learn
- What is Machine Learning and what does it encompass
- What are the 7 Steps of the Machine Learning Process
- What are the different Machine Learning types
- How is Machine Learning applied to the real world
- What are the main Data Mining techniques
- How to best set up the Python environment for Machine Learning
- What are the most important Python libraries for Machine Learning
And much more…
456 pages, Kindle Edition
Published January 14, 2021
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