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

Homepage

https://www.udemy.com/course/complete-python-megacourse-beginner-to-expert/