This book has two parts :

Part I      The Basics

In this part, readers will be able to learn the basic of Python programming. , creating a foundation for general programming languages, which is applicable for programming in any language.

Chapter 1  Introduction : Readers learn to Install Python.Including Python packages, modules. and Code editor (Visual Studio Code).

Chapter 2 Data Types : Readers learn of data types defined in the Python programming language, among others.

Chapter 3 Lists/Dictionaries/Sets/Tuples : Python has lists, dictionaries, sets and tuples, all of which are used to define as much data as desired to be stored in a single variable, making it possible to work with large amounts of data using just a few lines of code.

Chapter 4  Operators : In Python, operators are generally used perform operations on values and variables using for logical and mathematical operations.

Chapter 5  Conditional Statements : Conditional statements allow programmers to specify conditions that use the value of a variable or the result of a comparison to perform a desired statement. Python has a number of interesting techniques for using them.

Chapter 6  Functions : In this chapter, readers learn how to define and call functions, as well as pass and return data.

Chapter 7  Modules : Readers learn how to create their own modules and how to import other modules. 

Chapter 8  String Formatting : Readers can use String formatting to format strtings within strings, causing variable values to be passed into the strings.

Chapter 9  Object-oriented programming (OOP) : Python is an object-oriented programming language. Readers will learn to create classes (with method or attributes), objects and relationships between classes (Inheritance, Association, Composition, and Aggregation)

Chapter 10 Try…Exception : Python has a try…exception that reader can use to easily catch errors.

Chapter 11 File Management, with…as and JSON : Reader will learn how to use functions for creating, reading, updating and deleting files, with..as, and to read and write JSON files. 

Part II Software Development Projects

In Part II, readers will be introduced to four types of projects developed with Python so that readers can practice and adapt them for their own work. A brief description of the four types of projects is as follows.

Project 1 Game

In this project, readers will use the Pygame package to develop a 2D game that lets players shoot alien ships to explode. Make it in time before the alien ship drops down to the player's place. and must dodge alien bombs as they drop, and readers will be able to use the examples the author created to make changes to the program to make it more understandable at the end of the project. Readers will learn skills that will help you develop your own 2D games in Pygame.

As for Python, there are many game program developers who use it to develop famous games such as Pacman, Snake, Tic-tac-toe, etc., which readers can use to modify it in developing their own games as well.

Project 2 Web Application

In this project, reader will be able to use the Django package to easily develop a Web Application. Python, itself has a database that can be used without having to install any database. In this section, readers will be able to learn how to develop programs that can update, add, edit, and delete data.

Project 3 Data Analysis

In this project, readers will learn how to use beautiful and functional data visualization using matplotlib and pygal in a way that can be used for data analysis which is very useful in research. Various business jobs You can also create map presentations.

Project 4 Artificial Intelligence (AI)

In this project, readers will learn about Artificial Intelligence using matplotlib, scipy, scikit-learn, numpy package and Python development tools. The following Artificial Intelligence tools are available:

Mathematical Tools :

Statistics

• Mean

• Median

• Mode

• Standard Deviation

• Percentiles

   Creating data for testing

   Data Analysis

• Scatter Plot Analysis

• Linear Regression Analysis

• Polynomial Regression Analysis

• Multiple Regression Analysis

• Categorical Data Analysis

Data Mining

• Decision Tree

• Hierarchical Clustering

• K-Means

• Association Rules

Teaching and Testing Tools.