What you'll learn

Master Python fundamentals with confidence using knowledge from C/C++.
Transition easily from procedural programming to Python's object-oriented approach.
Learn how to utilize Python libraries for data science, web scraping, and more.
Develop Python programs and scripts that solve real-world problems.

Requirements

Basic understanding of programming, especially in C and C++.
A laptop or desktop with Python installed.

Description

Are you familiar with C and C++ programming languages and ready to dive into the world of Python? "Learn Python After C C++" is the ideal course for you to leverage your existing programming knowledge and transition smoothly into one of the most versatile and in-demand programming languages. Python has a simple syntax, dynamic libraries, and immense applications across various industries, from web development to machine learning. This course is designed to bridge the gap between low-level languages like C/C++ and Python's high-level functionality.In this course, we cover Python fundamentals in an organized and structured way, focusing on how your background in C and C++ will help you excel in Python. By the end, you'll have gained an in-depth understanding of Python and how it can enhance your career.Course Outline Chapter 1: Python Basics: Variables, Data Types, and OperatorsChapter 2: Control Structures: Loops, Conditional StatementsChapter 3: Functions in PythonChapter 4: Object-Oriented Programming in PythonChapter 5: Working with Libraries and ModulesChapter 6: File Handling and Exception ManagementChapter 7: Data Analysis with Pandas and NumPyWhy Learn Python After C C++?Python's simplicity allows for faster development, saving time and effort.High-level applications of Python provide more job opportunities in fields like AI and data science.Python integrates easily with C/C++, making it ideal for multi-language projects.Python's huge community ensures that there's plenty of support and resources available for continued learning.Benefits of Taking This CourseEnhance your programming portfolio with Python expertise.Gain more job opportunities in industries like data analysis, AI, and software development.Make complex programming simpler and more efficient.Achieve fluency in Python, a highly versatile language used by top tech companies.How to Make Money After Completing This CourseFreelance Python development for web and software projects.Work as a data analyst or machine learning specialist.Contribute to open-source projects and get paid for your contributions.Build Python-based products or apps and sell them online.30 Days Money-Back Guarantee: If you are not satisfied with the course, you can get a full refund within 30 days.Certificate: You will receive a course completion certificate, which you can showcase to potential employers.

Overview

Section 1: Chapter 01
Lecture 1 01 Introduction to Chapter 01
Lecture 2 02 Introduction to Python
Lecture 3 03 Python Environment Setup & Hello World Program
Lecture 4 04 In C Cpp Environment Setup
Lecture 5 05 Input Output Function in Python
Lecture 6 06 Important Concepts in python
Lecture 7 07 Variabls and Declaration Rules in Python
Lecture 8 08 Comments and its Types in Python
Lecture 9 09 C Cpp Variables Declare and Intialization
Lecture 10 10 Data Types in Python
Section 2: Chapter 02
Lecture 11 11 Introduction to Chapter 02 Python
Lecture 12 12 Decision Making in Python
Lecture 13 13 for LOOP in Python
Lecture 14 14 while Loop in Python
Lecture 15 15 C Cpp Loops
Lecture 16 16 Exercise 01 with Solution
Lecture 17 17 Exercise 02 with Solution
Lecture 18 18 Exercise 03 with Solution
Lecture 19 19 Exercise 04 with Solution
Lecture 20 20 Exercise 05 with Solution
Section 3: Chapter 03
Lecture 21 21 Introduction to Chapter 03
Lecture 22 22 Function in Python
Lecture 23 23 Return and Pass keyword in Function Python
Lecture 24 24 Arguments and Parameters in Python Function
Lecture 25 25 Function in C Cpp
Lecture 26 26 Keywords Arguments in Python Function
Lecture 27 27 Default Parameter
Lecture 28 28 Required Parameters in Python Function
Lecture 29 29 Exersise 01 with Solution
Lecture 30 30 Exersise 02 with Solution
Lecture 31 31 Exersise 03 with Solution
Section 4: Chapter 04
Lecture 32 32 Chapter 04 Outline Python OOP
Lecture 33 33 Python OOP Classes and Objects with Examples
Lecture 34 34 Python Data Members in Python OOP
Lecture 35 35 Python self Keyword in Python OOP
Lecture 36 36 Python Constructor and its Types
Lecture 37 37 Destructor in Python OOP
Lecture 38 38 Inheritance in Python OOP
Lecture 39 39 super Keyword in Python OOP
Lecture 40 40 Polymorphism with Examples
Lecture 41 41 Access Specifiers in Python OOP
Section 5: Chapter 05
Lecture 42 42 Python Chapter 05 Outline
Lecture 43 43 Modules and Libraries in Python
Lecture 44 44 Why use Libraries and Modules
Lecture 45 45 Common Python Standard Libraries
Lecture 46 46 Custom Modules in Python
Lecture 47 47 Managing External Libraries in Python
Lecture 48 48 Best Practices to Use External Python Libraries
Section 6: Chapter 06
Lecture 49 49 Chapter 06 Outlines
Lecture 50 50 Introduction to File Handling in Python
Lecture 51 51 Opening Reading Writing Closing a File in Python
Lecture 52 52 Append method in File Handling
Lecture 53 53 Working with Files Modes in Python
Lecture 54 54 Exception Handling in Python
Section 7: Chapter 07
Lecture 55 55 Chapter 07 Outlines
Lecture 56 56 Introduction to Data Analysis with Pandas and Numpy
Programmers familiar with C/C++ who want to learn Python.,Students seeking to enhance their programming portfolio.,Professionals looking to expand into Python for data science or web development.

Homepage:

https://www.udemy.com/course/outstanding-learn-python-programming-after-c-c/