Complete Python Megacourse: Beginner To Expert

Learn how to work with Python with this step-by-step course!

What you'll learn

The essential Python programming language

How to use Python professionally or for personal tasks

How to solve problems involving conditional statements

How to build programs using advanced Python features

Create games with Python like Rock paper scissors

Gain and improve your coding skills

How to build projects and applications like a Banking System from scratch

Create a portfolio of Python projects that will allow you to apply to developer jobs

Understand Python 2 and Python 3

Using lists, tuples, dictionaries, and sets to organize data and solve problems

Working with functions and strings to create reusable code and manipulate text

Requirements

No previous knowledge of Python required

A desire to learn!

A positive attitude!

Description

Learn programming in Python!Develop like a pro!Have you ever wanted to develop a solid programming skillset in Python?Programming is currently the most important knowledge you could have, and it will be from now on. From developing an app to creating the e-shop for your favorite brands, the things you can do with programming are endless. Python is ranked as the fastest growing programming language since 2022 and the demand for Pythoneers has not ceased to increase. Not only that you can use Python to improve your chances of finding a job, but you can also make use of it to automate your daily tasks either professionally or personally, and we’re here to teach you how.In this course, you will become familiar with several computer science concepts that we implement using Python. Therefore, both your problem-solving skills and coding abilities will be sharpened throughout this course to prepare you for the next step in your career. As a general-purpose programming language, Python is used in several fields, including Machine Learning, Data Analysis, Backend Systems, Web Scraping, and Automation. Before exploring each of these topics, we will develop the skills necessary to write Python code following proper practices.Our instructors have years of experience not only in programming, but also in teaching, and the expertly-crafted syllabus is designed to be easy to follow and thorough. We’ve even included plenty of practice problems and real-life projects. That’s why this is the only Python course you’ll ever need to start programming like a pro!After taking this course, you will be able to:Work professionally with PythonHandle files and dictionariesDevelop the first project for your start upCode professionally in PythonCreate your own Python programsDemonstrate your knowledge of Python programmingAnalyze the complexity of algorithms and implement sorting algorithms like selection sort, bubble sort, and insertion sort.Start developing your projects today!

Overview

Section 1: Introduction

Lecture 1 Welcome

Section 2: Introduction to Python

Lecture 2 Python Characteristics

Lecture 3 Python 2 vs Python 3

Lecture 4 Installation, Jupyter, and Demo

Section 3: Python Basics

Lecture 5 Taking Input Data from the User

Lecture 6 Output Formatting

Lecture 7 Math Library in Python Part I

Lecture 8 Math Library in Python Part II

Lecture 9 Random Module in Python

Lecture 10 Random Module - Game Demo

Lecture 11 Generating Sequences using Range in Python

Lecture 12 Python Variables and Data Types

Lecture 13 More on Python Variables

Section 4: Conditional Statements

Lecture 14 Truth Values and Simple Conditional Statements

Lecture 15 Problem Solving Involving Conditional Statements I

Lecture 16 Problem Solving Involving Conditional Statements II

Lecture 17 Rock Paper Scissors Game in Python

Lecture 18 Capitals Game in Python

Section 5: Iterative Statements

Lecture 19 Introduction

Lecture 20 For-Loops and While Loops

Lecture 21 Printing Shapes Using Loops

Lecture 22 Building Shapes with Numbers Using Loops

Lecture 23 Finding LCM, GCD and Binary Conversion

Lecture 24 Nested Loops Introduction

Lecture 25 Nested Loops and Pattern Finding

Lecture 26 Nested Loops and Narcissistic Numbers

Section 6: List and Tuples

Lecture 27 Mutability Versus Immutability

Lecture 28 Common Methods in Lists

Lecture 29 Tuple Basics, Copy and Deepcopy Methods

Lecture 30 Tuple Basics and Zip Method

Lecture 31 Inner Product and Sorting a List of Tuples

Lecture 32 Practice Problems I

Lecture 33 2-Dimensional Lists (List of Lists) Part I

Lecture 34 2-Dimensional Lists (List of Lists) Part II

Section 7: Dictionaries

Lecture 35 Introduction to Dictionaries

Lecture 36 Most Common Methods in Dictionaries

Lecture 37 Simple Manipulations with Dictionaries

Lecture 38 Dictionaries Practice Problems I

Lecture 39 Handling a List of Dictionaries

Lecture 40 List of Dictionaries and JSON objects

Lecture 41 Creating a JSON File Using a Dictionary of Dictionaries

Section 8: Sets in Python

Lecture 42 Nature of Sets and Methods in the Normal and Frozen Sets

Lecture 43 Working with Frozen Sets and Evaluating Mathematical Set Expressions

Section 9: Functions

Lecture 44 Introduction to Functions

Lecture 45 Translating a code snippet to a function Part I

Lecture 46 Translating a code snippet to a function Part II

Lecture 47 Translating a code snippet to a function Part III

Lecture 48 Translating a code snippet to a function Part IV

Lecture 49 Translating a code snippet to a function Part V

Section 10: Strings

Lecture 50 Introduction to Strings and Most Common Methods

Lecture 51 More on String Methods

Lecture 52 String Boolean Methods Part I

Lecture 53 String Boolean Methods Part II

Lecture 54 String Boolean Methods Part III

Lecture 55 String Boolean Methods Part IV

Lecture 56 String Boolean Methods Part V

Lecture 57 String Boolean Methods Part VI

Lecture 58 String Boolean Methods Part VII

Lecture 59 String Boolean Methods Part VIII

Lecture 60 String Boolean Methods Part IX

Section 11: Data Structures

Lecture 61 Linear Data Structures: Stacks, Push and Pop Operations

Lecture 62 Using Stacks to Check for Balanced Expressions

Section 12: File Handling

Lecture 63 Files Handling Part I

Lecture 64 Files Handling Part II

Lecture 65 Files Handling Part III

Lecture 66 Files Handling Part IV

Lecture 67 Files Handling Part V

Lecture 68 Files Handling Part VI

Section 13: Projects

Lecture 69 Dictionaries Mini Project 1

Lecture 70 Mini Project 2 Workspace Monitoring System Part I

Lecture 71 Mini Project 2 Workspace Monitoring System Part II

Lecture 72 Bisection Method

Lecture 73 Banking System I

Lecture 74 Banking System II

Lecture 75 Banking System III

Lecture 76 Banking System IV

Lecture 77 Banking System V

Lecture 78 Banking System VI

Lecture 79 Banking System VII

Lecture 80 Banking System VIII

Lecture 81 Banking System IX

Lecture 82 Banking System X

Lecture 83 Banking System XI

Lecture 84 Banking System XII

Lecture 85 Banking System XIII

Lecture 86 Banking System XIV

Lecture 87 Banking System XV

Section 14: Python Intermediate: Object Oriented Programming

Lecture 88 Introduction

Lecture 89 Class Design and Implementation

Lecture 90 Class Instantiation

Lecture 91 Class Methods and Inheritance

Lecture 92 Polymorphism

Lecture 93 Recap

Lecture 94 Combining OOP Concepts I

Lecture 95 Combining OOP Concepts II

Lecture 96 Objects Storage Through Pickling

Lecture 97 Exceptions and the Exception Class

Lecture 98 Project I Part 1

Lecture 99 Project I Part 2

Lecture 100 Project I Part 3

Lecture 101 Project I Part 4

Section 15: Algorithms Design and Analysis

Lecture 102 Recursion I

Lecture 103 Recursion II

Lecture 104 Recursion III

Lecture 105 Complexity Analysis I

Lecture 106 Complexity Analysis II

Lecture 107 Sorting Using Selection Sort

Lecture 108 Sorting Using Bubble Sort

Lecture 109 Sorting Using Insertion Sort

Lecture 110 Divide and Conquer

Lecture 111 Merge Sort Recursively

Lecture 112 Merge Sort Complexity Analysis

Lecture 113 Iterative Merge Sort

Section 16: Iterators and Generators

Lecture 114 Iterables and Iterators

Lecture 115 Generators

Lecture 116 Lambda Functions I

Lecture 117 Lambda Functions II

Lecture 118 Map, Filter, Reduce with List Comprehension I

Lecture 119 Map, Filter, Reduce with List Comprehension II

Section 17: CVS Files

Lecture 120 Open, Reading, Writing

Lecture 121 Manipulate Data

Lecture 122 CVS Module

Section 18: NumPy

Lecture 123 Installation and Must-Know Functions

Lecture 124 Broadcasting

Lecture 125 Statistical Functions

Section 19: Pandas

Lecture 126 Installation and Introduction

Lecture 127 Series, Mutability, Initializing with Dictionaries

Lecture 128 Series, NumPy

Lecture 129 Statistical Functions and Indexing Using loc/iloc

Lecture 130 Filtering Dataframes

Lecture 131 Slicing Dataframes and the Group By Method

Lecture 132 Group By, Pivot and Sorting Methods

Lecture 133 Pivot vs Melt Methods

Lecture 134 Concat and Merge Methods I

Lecture 135 Concat and Merge Methods II

Lecture 136 Practice I

Lecture 137 Str and Replace Methods

Lecture 138 Reindex, Query, Dropna, and Fillna Methods

Lecture 139 Practice II

Lecture 140 Shift, iat, and Sub Methods

Lecture 141 Recap I

Lecture 142 Recap II

Lecture 143 Visualizations: Seaborn Library Part I

Lecture 144 Visualizations: Seaborn Library Part II

Section 20: Databases

Lecture 145 SQLite Intro

Lecture 146 Querying from Python

Lecture 147 Setting Up Cassandra I

Lecture 148 Setting Up Cassandra II

Lecture 149 IG Stream API Practice

Lecture 150 Grafana Introduction

Section 21: Python Advanced Add-ons

Lecture 151 Introduction

Section 22: HTML

Lecture 152 Introduction to HTML

Lecture 153 HTML “Hello World”

Lecture 154 Elements

Lecture 155 Attributes

Lecture 156 Lists & Tables

Lecture 157 Styles

Lecture 158 Formatting

Lecture 159 Classes

Lecture 160 Hyperlinks

Lecture 161 Forms

Lecture 162 Buttons

Lecture 163 Iframes

Lecture 164 Style Guide

Lecture 165 Summary

Lecture 166 Quiz

Section 23: CSS

Lecture 167 Introduction to CSS

Lecture 168 Syntax

Lecture 169 Selectors

Lecture 170 CSS Box Model

Lecture 171 Text

Lecture 172 Fonts

Lecture 173 Icons

Lecture 174 Links

Lecture 175 Lists and Tables

Lecture 176 Transforming and Positioning Elements

Lecture 177 Important

Lecture 178 Math Functions

Lecture 179 Variables

Lecture 180 Media Queries

Lecture 181 Flexbox

Lecture 182 Summary

Lecture 183 Quiz

Section 24: Project I

Lecture 184 Demo

Lecture 185 Setup

Lecture 186 Layout

Lecture 187 Placing the Elements

Lecture 188 Assets and Icons

Lecture 189 Hyperlinks

Lecture 190 Colgroup

Lecture 191 Styling

Lecture 192 Bringing It Together

Lecture 193 Finished Product

Section 25: Flask

Lecture 194 Introduction to Flask

Lecture 195 Routes and Templates

Lecture 196 Static Files

Lecture 197 Request Object and HTTP Methods

Lecture 198 Template Inheritance

Lecture 199 Form Data

Lecture 200 Cookies and Sessions

Lecture 201 Redirects, Errors, and Flash Messages

Lecture 202 Extensions

Lecture 203 Mail

Lecture 204 WTF

Lecture 205 SQL Alchemy

Lecture 206 Deployment

Lecture 207 Summary

Section 26: Project II

Lecture 208 Introduction and Demo

Lecture 209 Folder Structure

Lecture 210 Creating a Flask App

Lecture 211 Linking Static Files

Lecture 212 Creating the Database

Lecture 213 Flask Login

Lecture 214 Login Functionality

Lecture 215 Creating Forms

Lecture 216 User Product Methods

Lecture 217 Product Routes

Lecture 218 Flash Messages

Lecture 219 Wrapping Up

Lecture 220 Last Words

Anyone who wants to learn software development and programming- no experience needed!,Programmers who want to switch languages to Python,Anyone who has started working with Python but wants to level up their skills,Anyone who wants to start building their own websites and web apps