Master Advanced Python Programming with Practical Examples (2024)

2024 Advanced Python Programming with Coding Examples

Exploring the Depths: Advanced Python Programming with Hands-On Coding Examples

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Last Updated: 2024-11-26 07:11:23 English Course Type: Self Learning

Python programming
OOP with Python
Advanced Functional Programming
Regular Expression
Data base with Python

Welcome to the 'Advanced Python Programming'

"Welcome to the 'Advanced Python Programming' course, where your journey from Python proficiency to mastery begins. This course is meticulously designed to elevate your Python skills to an advanced level, equipping you with a comprehensive toolkit to tackle complex programming challenges and explore the diverse applications of Python across various domains. Delve deeper into functional programming paradigms, master the intricacies of object-oriented programming, harness the power of regular expressions, databases, file I/O, and popular Python libraries like NumPy, Pandas, and Matplotlib. Moreover, uncover the art of web scraping and dive into web frameworks like Django. Whether you're a seasoned developer aiming to enhance your expertise or an aspiring data scientist seeking to unlock Python's full potential, this course empowers you with the expertise needed to excel in software development, data analysis, web development, and beyond. Join us on this enriching learning journey and unlock the door to limitless possibilities with Python."

Here are the specific skills imparted by the "Advanced Python Programming" course through its curriculum, along with the respective fields where students can apply those skills:

Functional Programming and Python Basics:

Skills: Understanding of functional programming concepts, lambda functions, map, filter, reduce functions, generators, iterators, and decorators.

Applications: Software development, data analysis, algorithmic programming, and code optimization.

Object-Oriented Programming (OOP):

Skills: Mastery of OOP principles, including classes, objects, inheritance, polymorphism, encapsulation, and access specifiers in Python.

Applications: Building modular and scalable applications, designing software systems, creating reusable code, and implementing design patterns.

Regular Expressions:

Skills: Proficiency in using regular expressions in Python, understanding special sequences, quantifiers, and sets.

Applications: Text processing, data validation, search operations, pattern matching, and manipulating textual data efficiently.

Database Operations:

Skills: Hands-on experience with connecting to databases, performing CRUD (Create, Read, Update, Delete) operations, utilizing SQL queries, and managing databases using Python.

Applications: Data management, database-driven applications, web development, data storage, and retrieval.

Input and Output Operations:

Skills: Reading and writing different file formats like CSV, Excel, and JSON using Python, enabling data interchangeability.

Applications: Data analysis, data manipulation, data migration, report generation, and working with various data sources.

Popular Python Libraries/Frameworks:

Skills: Proficiency in using key libraries like NumPy, Pandas, Matplotlib for numerical computing, data analysis, and data visualization, as well as an introduction to web frameworks like Django.

Applications: Scientific computing, data manipulation, statistical analysis, visualization, and web development.

Web Scraping:

Skills: Understanding of web scraping techniques using Beautiful Soup, HTML, and CSS structure, setting up scraping environments, and parsing web pages.

Applications: Data collection, content aggregation, market research, automated data extraction, and analysis from websites.

Students equipped with these skills can apply their knowledge in various domains and fields such as:

Software Development: Building scalable applications, implementing efficient algorithms, and utilizing modular programming techniques.

Data Analysis and Science: Analyzing and visualizing data, manipulating datasets, conducting statistical analysis, and deriving insights.

Web Development: Creating web applications, handling databases, integrating APIs, and scraping data for content generation.

Automation and Scripting: Automating repetitive tasks, system administration, and scripting workflows to improve productivity.

Research and Academia: Implementing algorithms, conducting experiments, processing data, and publishing research findings.

Business and Industry: Solving real-world problems, optimizing processes, and making data-driven decisions across various sectors.

The comprehensive skill set acquired from this course enables students to apply Python in diverse professional settings, making them proficient in addressing real-world challenges and contributing effectively in their respective fields.

Basic Python Programming

Intermediate Python Programmers: Those who have a basic understanding of Python and want to expand their knowledge to more complex and powerful features.
Developers and Programmers: Professionals seeking to enhance their Python skills for more sophisticated programming tasks, including those working in software development, data analysis, or web development.
Students or Learners: Individuals studying computer science, software engineering, data science, or related fields interested in advancing their Python proficiency.
Python Enthusiasts: Hobbyists or enthusiasts eager to explore the intricacies of Python, functional programming, object-oriented programming (OOP), databases, web scraping, and popular Python libraries.
Aspiring Web Developers: Those aiming to understand web development with Python using frameworks like Django and exploring web scraping techniques for various purposes.
Data Analysts and Data Scientists: Professionals interested in utilizing Python's data manipulation, visualization libraries like NumPy, Pandas, Matplotlib, and learning how to work with databases for data storage and retrieval.

Section 1 : Chapter 01 3 Lectures 00:00:00
Lecture 1 :
Advanced Python Chapter 01 Preview
Lecture 2 :
What is Advanced Python
Lecture 3 :
Why Learn Advanced Python
Section 2 : Chapter 02 11 Lectures 00:00:00
Lecture 1 :
Advanced Python Chapter 02
Lecture 2 :
Pure Function in Advanced Python
Lecture 3 :
Higher Order function in Advanced Python
Lecture 4 :
Lambda Function in Advanced Python
Lecture 5 :
Map function in Python
Lecture 6 :
Map Examples in Python
Lecture 7 :
Filter function in Python
Lecture 8 :
Filter Function Examples in Python
Lecture 9 :
Reduce Function in Python
Lecture 10 :
Generator Function in Python
Lecture 11 :
Decorator Function in Python
Section 3 : Chapter 03 17 Lectures 00:00:00
Lecture 1 :
Advanced Python Chapter 02
Lecture 2 :
Introduction to OOP
Lecture 3 :
Class Creation in Python
Lecture 4 :
Object in OOP Python
Lecture 5 :
Data Members and Member functions
Lecture 6 :
Self Keyword in OOP
Lecture 7 :
Constructor in OOP Python
Lecture 8 :
Destructor in OOP Python
Lecture 9 :
Inheritance in OOP Python
Lecture 10 :
Single Inheritance in OOP Python
Lecture 11 :
Multiple inheritance in OOP Python
Lecture 12 :
Multi Level Inheritance in OOP Python
Lecture 13 :
Herarchical Inheritance in OOP Python
Lecture 14 :
Super Keyword in OOP Python
Lecture 15 :
Polymorphism in OOP Python
Lecture 16 :
Private Access Specefiers in OOP
Lecture 17 :
Protected and Public Access Specefiers in OOP
Section 4 : Chapter 04 15 Lectures 00:00:00
Lecture 1 :
Advanced Python Chapter 04 Outlines
Lecture 2 :
Introduction to Regular Expression
Lecture 3 :
Regular Expression Working
Lecture 4 :
Special Sequences in Regex
Lecture 5 :
d and D Special Sequence in Regular Expression
Lecture 6 :
word Character in Regex
Lecture 7 :
White space char in Regex
Lecture 8 :
dot pattern in regex
Lecture 9 :
More special Sequence in regex
Lecture 10 :
word boundry in regex
Lecture 11 :
SET in regex
Lecture 12 :
findall function in regex
Lecture 13 :
search function in regex
Lecture 14 :
split function in regex
Lecture 15 :
sub function in regex
Section 5 : Chapter 05 15 Lectures 00:00:00
Lecture 1 :
Chapter 05 Advanced Python Outline
Lecture 2 :
DB and DBMS Introduction
Lecture 3 :
DataBase Python Libraries
Lecture 4 :
Setup PyMySQL library
Lecture 5 :
Make Connection with DataBase
Lecture 6 :
Creating Database
Lecture 7 :
Creating Table in Datbase
Lecture 8 :
DB and Table creation Examples
Lecture 9 :
INSERT Query with Examples
Lecture 10 :
Paramterized INSERT Query with Examples
Lecture 11 :
Select Query with Examples
Lecture 12 :
UPDATE Query with Examples
Lecture 13 :
DELETE Query with Examples
Lecture 14 :
LIMIT Clause
Lecture 15 :
Where Clause
Section 6 : Chapter 06 6 Lectures 00:00:00
Lecture 1 :
Chapter 06 Advanced Python Outline
Lecture 2 :
Basics Input Output Operations
Lecture 3 :
CSV file Input Output Operations
Lecture 4 :
Excel File Input Output Operations
Lecture 5 :
JSON file Input operation
Lecture 6 :
JSON data Output operation
Section 7 : Chapter 07 6 Lectures 00:00:00
Lecture 1 :
Chapter 07 Advanced Python Outline
Lecture 2 :
Introduction to Numpy Library
Lecture 3 :
Introduction to Pandas Library
Lecture 4 :
Introduction to Matplotlib
Lecture 5 :
Introduction to Django
Lecture 6 :
Excel OpenPyXl Library
Section 8 : Chapter 08 14 Lectures 00:00:00
Lecture 1 :
Chapter 08 Advanced Python Outline
Lecture 2 :
Web Scraping Introduction and Importance
Lecture 3 :
Web Scraping Libraries
Lecture 4 :
Requirements for Web Scraping
Lecture 5 :
HTML and CSS Introduction
Lecture 6 :
Setup for Beautiful Soup
Lecture 7 :
Web Scraping without requests module
Lecture 8 :
08 Web Scraping with requests module
Lecture 9 :
Beautiful soup with and without requests module
Lecture 10 :
Web Scraping Techniques
Lecture 11 :
Web Scraping Exersise 01
Lecture 12 :
Web Scraping Exersise 02
Lecture 13 :
Web Scraping Exersise 03
Lecture 14 :
Web Scraping Exersise 04

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Faisal Zamir,

506892 Course Views

29 Courses

Hello, my name is Faisal Zamir and I am a Master of Computer Science with over 7 years of experience in teaching. I have a passion for teaching and have dedicated my career to educating students on various topics related to web designing, web development, and programming languages such as Python, PHP, JavaScript, C++, C#, and more. As an instructor, I believe in providing students with a comprehensive learning experience that goes beyond just theory. That's why I always provide programming examples, discussion (Q&A), quizzes, assignments, problems with solutions, exercises, and more to ensure that my students have a hands-on approach to learning. My courses are designed to provide students with lifetime access to all course materials and resources, as well as ongoing support. I am committed to helping my students achieve their goals, whether it's to improve their skills for personal or professional reasons. In addition to teaching, I have also worked on various projects in the field of computer science and have acquired practical experience in implementing programming concepts in real-world scenarios. I bring this experience into my teaching to provide my students with a practical and relevant education. Thank you for considering my courses and I look forward to helping you achieve your goals in the world of computer science.