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Complete Python Megacourse: Beginner To Expert - Panter - 02.01.2024 Complete Python Megacourse: Beginner To Expert Published 11/2023 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 21.22 GB | Duration: 60h 1m 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 |