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Python Crash Course
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Do you want to learn Python Programming well and fast?Are you looking for the best Python for Data Analysis and Analytics course?
If yes, then this Python Crash Course is for you. This is the most complete Python guide with 2 Manuscripts in 1 book:
1-Python For Beginners
2- Python Programming
A great opportunity: Simplicity, Best Order and Selection of topics to Learn Fast and Selected Practice Exercises and Examples.
In Manuscripts 1 "Python For Beginners" you'll learn:
- 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 2 "Python programming" you'll learn:
- 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...
Click the BUY button and download the book now to start learning well and fast- Utbildningsresurser & tekniska hjälpmedel, datorstött lärande (CAL, computer-aided learning) (inom Pedagogik)
- Programmerings- & skriptspråk: allmänt (inom Programmering)
- Spelutveckling & spelprogrammering (inom Programmering)
- Programmering (inom Datorer & IT)
- Spel, IT & multimedia: Guider (inom Datorer & IT)
- Algoritmer & datastrukturer (inom Programmering)
- Informationsutvinning (data mining) (inom Databaser)
- Bildbehandling & digitala mediaprogram (inom Datorer & IT)
- Webbtjänster (inom Webbprogrammering)
- Webbprogrammering (inom Programmering)
- Microsoft-programmering (inom Programmering)
- Dataanalys (inom Forskningsinformation)
- Grafikprogrammering (inom Programmering)
- Objektorienterad programmering (OOP) (inom Programmering)
- Forskningsinformation (inom Naturvetenskap & Teknik)
- Agile programming (inom Programmering)
- Datorer: maskinvara (inom Datorer & IT)
- .Net-programmering (inom Microsoft-programmering)
- 2D-grafik: spelprogrammering (inom Spelutveckling & spelprogrammering)
- Programkoncept / att lära sig programmering (inom Programmering)
- Unified Modeling Language (UML) (inom Programvaruteknik)
- Windows-programmering (inom Microsoft-programmering)
- Kompilatorer (inom Programmering)
- Funktionell programmering (inom Programmering)
- Databasprogrammering (inom Programmering)
- Programvarutestning & verifiering (inom Programvaruteknik)
- Mac-programmering (inom Programmering)
- Nätverksprogrammering (inom Programmering)
- Nivådesign: spelprogrammering (inom Spelutveckling & spelprogrammering)
- Objektorienterad programvaruteknik (inom Programvaruteknik)
- Extremprogrammering (inom Programmering)
- Programvaruteknik (inom Programmering)
- Programmering för handdatorer (inom Programmering)
- Datorspel: strategiguider (inom Spel, IT & multimedia: Guider)
- 3D-grafik: spelprogrammering (inom Spelutveckling & spelprogrammering)
- Aspektprogrammering, aspektorienterad programmering (AOP) (inom Programmering)