Python Programming Bootcamp: From Basics To Expert (2025)
Published 2/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 7.46 GB | Duration: 21h 15m
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.
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