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  • 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.
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  • Section 1 : Chapter 01 3 Lectures

    • 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

    • 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

    • 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

    • 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

    • 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

    • 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

    • 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

    • 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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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.
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