Python basics, data structures, OOP, functional programming, API , Data Exploration

What you'll learn

Master Python Basics: Learn Python installation, syntax, variables, operators, and core programming concepts like loops and conditionals.

Explore Python Data Structures: Gain proficiency in using strings, tuples, lists, dictionaries, and their operations.

Understand Python Functions: Learn to create functions with arguments, return values, default values, and variable-length arguments.

Handle Files and Exceptions: Develop skills in file handling and managing exceptions for robust programming.

Utilize Python Libraries: Explore special functions, random module, collections, and modules like datetime, time, and pytz.

Implement Advanced Techniques: Work with regular expressions, object-oriented programming (OOP), and Python's operating system interfaces.

Work with Multithreading and Multiprocessing: Learn to optimize tasks using Python threading and multiprocessing.

Requirements

No Prior Programming Experience Needed: This course is designed for absolute beginners as well as those looking to deepen their Python knowledge.

A Computer with Internet Access: Learners need a Windows, macOS, or Linux computer with an active internet connection for downloading tools and materials.

Basic Computer Skills: Familiarity with using a computer, navigating files, and installing software is helpful but not mandatory.

Curiosity and Willingness to Learn: A positive mindset and eagerness to explore programming concepts will help you succeed in this course.

Description

This course is designed to provide a thorough understanding of Python programming, starting from the basics and progressing to advanced concepts. Whether you are a beginner or an experienced programmer looking to enhance your skills, this course will equip you with the knowledge and practical experience needed to master Python. The course is structured to cover a wide range of topics, ensuring a holistic learning experience.Introduction to Python and InstallationThe course begins with an introduction to Python, highlighting its simplicity and versatility. You will learn how to install Python on different operating systems, including Windows and Linux. We will also cover the use of Virtualenv, a tool to create isolated Python environments, which is essential for managing dependencies and avoiding conflicts between projects.Basic Python Syntax and VariablesNext, we delve into the basic syntax of Python, including the use of backslashes, strings inside quotes, escape sequences, and formatted output using f-strings. You will also learn about Python variables and the assignment statement, which are fundamental to writing any Python program.Operators and Control StatementsThe course then moves on to Python operators, which are used to perform operations on variables and values. You will learn about control statements, including if and else statements, which allow you to control the flow of your program based on certain conditions.Loops and Control FlowWe will explore different types of loops in Python, including for loops and while loops, which are used to repeat a block of code multiple times. You will also learn about the break, continue, and pass statements, which provide additional control over the flow of your loops.Data Structures: Strings, Tuples, Lists, and DictionariesThe course covers essential Python data structures such as strings, tuples, lists, and dictionaries. You will learn how to manipulate strings using subscript operators, slicing, and various string methods. For tuples and lists, we will cover accessing values, indexing, slicing, updating, and using built-in functions like max() and min(). Additionally, you will learn about dictionary operations, functions, and methods, which are crucial for handling key-value pairs.Functions and ModulesFunctions are a cornerstone of Python programming, and this course will teach you how to define and use functions with arguments, return values, default arguments, and variable-length arguments. You will also learn about the global statement and the scope of variables. The course will introduce you to Python modules and packages, including how to import and locate modules, and how to create your own packages.Exception Handling and File I/OException handling is a critical aspect of robust programming. You will learn how to use try-except blocks, handle multiple exceptions, and raise your own exceptions. The course also covers file input/output operations, including reading from and writing to text files, and using the Python Pickle module for serialization and deserialization.Advanced Topics: Lambda, Map, Filter, and ReduceThe course delves into advanced topics such as lambda functions, and the map, filter, and reduce functions, which are powerful tools for functional programming. You will also learn about special functions like repr(), sorted(), isinstance(), len(), dir(), zip(), sum(), and eval().Random Module and CollectionsWe will explore the Python Random module, which provides functions for generating random numbers and making random choices. The course also covers the Collections module, including Counter and Deque, which are useful for counting and managing collections of items.Date and Time HandlingHandling dates and times is a common requirement in programming. This course will teach you how to work with the Time, Datetime, and Pytz modules to manage and manipulate date and time data effectively.Regular Expressions and OOPRegular expressions are a powerful tool for text processing, and you will learn how to use them in Python with functions like match(), search(), sub(), and findall(). The course also covers Object-Oriented Programming (OOP) concepts, including classes, objects, inheritance, method overriding, operator overloading, and private variables.Operating System Interfaces and LoggingYou will learn how to interact with the operating system using Python's os module, which provides functions for file and directory operations. The course also covers Python logging, which is essential for debugging and monitoring your applications.Concurrency: Threading, Multiprocessing, and SubprocessThe course introduces you to concurrent programming in Python, covering threading, multiprocessing, and the subprocess module. These concepts are crucial for writing efficient and scalable applications.Configuration and DecoratorsYou will learn how to use the Configparser module to avoid hardcoding configuration values in your code. The course also covers decorators and generators, which are advanced features that can enhance the functionality and readability of your code.Data Exploration with Pandas, Numpy, and MatplotlibData exploration is a key skill in data science, and this course will teach you how to use Pandas for data manipulation, Numpy for numerical computations, and Matplotlib for data visualization.Python Interaction with MySQL and Web APIsFinally, the course covers how to interact with MySQL databases using Python, and how to work with Web APIs to fetch and manipulate data from the web.By the end of this course, you will have a comprehensive understanding of Python programming, from basic syntax to advanced concepts, and you will be well-equipped to tackle real-world programming challenges.

Overview

Section 1: Introduction

Lecture 1 Introduction : Topics of Entire course

Lecture 2 Features of Python

Section 2: Python Installation and Editors

Lecture 3 Installation of Python in Windows

Lecture 4 Python in Linux and Virutalenv

Lecture 5 Editors

Section 3: Python Basic Syntaxes, Variable, and Operators

Lecture 6 Python print statement and triple quotes

Lecture 7 Variables

Lecture 8 Operator

Lecture 9 Type casting

Section 4: Python Control statement

Lecture 10 If and else statement

Lecture 11 elif statement

Section 5: Loop and break, continue and else statement

Lecture 12 loop and for loop

Lecture 13 Break, continue and else statement

Lecture 14 While loop

Section 6: String

Lecture 15 What is string and string indexing

Lecture 16 String Slicing and string functions

Lecture 17 String method part 1

Lecture 18 String method part 2

Lecture 19 String exercise

Section 7: Tuple

Lecture 20 Tuple introduction, indexing, slicing, packing and unpacking

Lecture 21 Tuple methods and loop over the tuple

Section 8: List , List methods, list compression

Lecture 22 Introduction of list , List indexing and slicing

Lecture 23 List methods

Lecture 24 List sort method

Lecture 25 List Comprehension

Section 9: Dictionary

Lecture 26 Dictionary and its usefulness

Lecture 27 Dictionary method part 1

Lecture 28 Dictionary method part 2

Lecture 29 Dictionary comprehension and Exercises

Section 10: Sets

Lecture 30 Sets and its use case

Section 11: File Handling

Lecture 31 Reading file

Lecture 32 Writing files and appending file

Lecture 33 Placing pointer using seek and tell methods

Lecture 34 Pickle module, saving complex data structure

Section 12: Function

Lecture 35 Function and Default argument

Lecture 36 Variable length argument *args and **kwargs

Lecture 37 Call by Reference, Local and Global variables

Section 13: Modules

Lecture 38 Creating and Importing modules

Lecture 39 Locating Module

Lecture 40 Packages

Section 14: Time

Lecture 41 Time module

Lecture 42 Datetime module and dealing with timezones

Section 15: Exception handling

Lecture 43 Need of Exception handling and how to handle Errors

Lecture 44 Else , finally statement and custom exception

Lecture 45 Traceback module to know exact error

Section 16: Collections module

Lecture 46 Counter

Lecture 47 Deque

Lecture 48 Named tuple

Section 17: Random module

Lecture 49 Random functions

Lecture 50 Exercise

Section 18: Python Special Functions

Lecture 51 Lambda and Filter function

Lecture 52 Map and Reduce

Lecture 53 Eval and Isinstance

Lecture 54 repr and sum

Section 19: Class

Lecture 55 Class, objects, constructor and instance variables

Lecture 56 Class variables

Lecture 57 Class method

Lecture 58 Inheritance, Method overriding

Lecture 59 Multiple and Multilevel Inheritance

Lecture 60 Operator overloading

Lecture 61 Static method

Lecture 62 Private method and Private variables

Lecture 63 Property, setter, deleter

Lecture 64 Abstract class

Lecture 65 __call__ method

Lecture 66 __new__ method creating singleton class

Lecture 67 class exercise, making new class from existing class

Section 20: Regular expression

Lecture 68 Regular expression, re module and function of re module

Lecture 69 Regular expression special characters

Lecture 70 Regular expression back slash / characters

Lecture 71 Regular expression exercises

Section 21: Thread

Lecture 72 Thread

Lecture 73 Thread locks

Lecture 74 Thread Rlock

Lecture 75 Daemon Thread

Lecture 76 Global Interpreter Lock (GIL)

Lecture 77 IO bound and CPU bound task

Lecture 78 Queue and Queue With Thread

Lecture 79 Thread with Queue, producer and consumer problem

Section 22: Multiprocessing

Lecture 80 Multiprocessing

Lecture 81 Multiprocessing communication

Section 23: Asynchronous Programming

Lecture 82 Asynchronous Programming using Async and Await key words

Lecture 83 Solving Producer and Consumer problem using Asynchronous Programming

Section 24: OS module and Subprocess

Lecture 84 Exploring the OS with OS module

Lecture 85 OS walk and system command

Lecture 86 Subprocess

Section 25: ArgumentParser module

Lecture 87 Command line parser and Argument parser

Lecture 88 Argument parser options

Section 26: Input and output to program

Lecture 89 ConfigParser Module

Lecture 90 Logger

Section 27: Special topics

Lecture 91 Decorator

Lecture 92 Generator

Section 28: Data Exploration

Lecture 93 Numpy, creating array and saving arrays

Lecture 94 Pandas, Creating dataframe and pandas series

Lecture 95 Pandas, handling missing values

Lecture 96 Changing values using replace, map, and apply

Lecture 97 Aggregation functions using groupby and setting indexes

Lecture 98 Filtering row using filter, and query

Lecture 99 Concatenating and merging of two data-frame using Pandas

Lecture 100 Find Correlation between two Variable using Pandas

Lecture 101 Visualise the data-frame using Matplotlib

Section 29: Python with Database MYSQL

Lecture 102 Creating connection

Lecture 103 Managing connection using Singleton class and Get, insert data operations

Section 30: Web API

Lecture 104 What is web API

Lecture 105 Introduction of FastAPI, Get Request

Lecture 106 FastAPI handling Post request

Lecture 107 Getting data from Database using FastAPI

Lecture 108 FastAPI Async Programming

Lecture 109 Authentication using API key

Section 31: Exercise

Lecture 110 Sort a list

Lecture 111 Merging list

Lecture 112 Project: Search for a Specific String in Files Within a Given Folder

Beginners in Programming: Individuals with little to no programming experience who want to start their coding journey with Python.,Aspiring Python Developers: Students and professionals looking to master Python for software development, data analysis, or automation.,Professionals Switching to Python: Developers or IT professionals familiar with other programming languages who want to transition to Python.