Python | Python Programming Language Course Without Coding

Python - Learn Python Programming Language Basics without coding with educational, short lectures & quizzes in a fun way

What you'll learn

Python is a general-purpose, object-oriented, high-level programming language.

Python Introduction

First Step to Coding

Using Quotation Marks in Python Coding

Introduction to Basic Data Structures in Python

Performing Assignment to Variables

Performing Complex Assignment to Variables

Type Conversion

Arithmetic Operations in Python

Examining the Print Function in Depth

Escape Sequence Operations

Boolean Logic Expressions

Examining Strings Specifically

Methods in Strings

Indexing and Slicing Character String

Complex Indexing and Slicing Operations

String Formatting with Arithmetic Operations

String Formatting With % Operator

String Formatting With String .Format Method

String Formatting With f-string Method

Data Structures-Creation of List

Reaching List Elements – Indexing and Slicing

Adding & Modifying & Deleting Elements of List

Adding and Deleting Elements to List with Methods

Adding and Deleting by Index in List

List Methods

Creation of Tuple

Reaching Tuple Elements Indexing And Slicing

Data Structures-Creation of Dictionary

Reaching Dictionary Elements

Adding & Changing & Deleting Elements in Dictionary

Dictionary Methods

Data Structures-Creation of Set

Adding & Removing Elements Methods in Sets

Difference Operation Methods In Sets

Intersection & Union Methods In Sets

Asking Questions to Sets with Methods

Input Functions

Structure of “if” Statements

Structure of “if-else” Statements

Structure of “if-elif-else” Statements

Structure of Nested “if-elif-else” Statements

Coordinated Programming with “IF” and “INPUT”

Ternary Condition

For Loop in Python

Using Conditional Expressions and For Loop Together

List Comprehension

While Loop in Python

Break & Continue Command

Meeting with Functions

Return Expression in Functions

Write Docstring in Function

Using Functions and Conditional Expressions Together

Arguments and Parameters

Built-in Functions

Requirements

A working computer (Windows, Mac, or Linux)

No prior knowledge of Python for beginners is required

Motivation to learn the Python which is the second largest number of job postings relative program language among all others

Curiosity for python programming language

Nothing else! It’s just you, your computer and your ambition to get started today

Description

Welcome to my " Python | Python Programming Language Course Without Coding " course.Python - Learn Python Programming Language Basics without coding with educational, short lectures & quizzes in a fun wayPython is a general-purpose, object-oriented, high-level programming language. Whether you work in artificial intelligence or finance or are pursuing a career in web development or data science, Python is one of the most important skills you can learn.Python instructors at OAK Academy specialize in everything from software development to data analysis and are known for their effective, friendly instruction for students of all levels.Python's simple syntax is especially suited for desktop, web, and business applications. Python's design philosophy emphasizes readability and usability. Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization. The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks. Python, machine learning, Django, python programming, ethical hacking, machine learning python, python Bootcamp, data science, data analysisDo you want to learn one of the employer’s most requested skills? If you think so, you are at the right place. We've designed for you "Python | Python Programming Language Course Without Coding” a straightforward course for the Python programming language.In the course, you will have down-to-earth way explanations of hands-on projects. With my course, you will learn Python Programming step-by-step. I made Python 3 programming simple and easy with exercises, challenges, and lots of real-life examples.This Python course is for everyone!My "Python: Learn Python with Real Python Hands-On Examples" is for everyone! If you don’t have any previous experience, not a problem! This course is expertly designed to teach everyone from complete beginners, right through to professionals ( as a refresher).Why Python?Python is a general-purpose, high-level, and multi-purpose programming language. The best thing about Python is, that it supports a lot of today’s technology including vast libraries for Twitter, data mining, scientific calculations, designing, back-end server for websites, engineering simulations, artificial learning, augmented reality and what not! Also, it supports all kinds of App development.No prior knowledge is needed!Python doesn't need any prior knowledge to learn it and the Ptyhon code is easy to understand for beginners.What you will learn?In this course, we will start from the very beginning and go all the way to programming with hands-on examples . We will first learn how to set up a lab and install needed software on your machine. Then during the course, you will learn the fundamentals of Python development likePython IntroductionFirst Step to CodingUsing Quotation Marks in Python CodingIntroduction to Basic Data Structures in PythonPerforming Assignment to VariablesPerforming Complex Assignment to VariablesType ConversionArithmetic Operations in PythonExamining the Print Function in DepthEscape Sequence OperationsBoolean Logic ExpressionsExamining Strings SpecificallyMethods in Strings-1Methods in Strings-2Methods in Strings-3Indexing and Slicing Character StringComplex Indexing and Slicing OperationsString Formatting with Arithmetic OperationsString Formatting With % OperatorString Formatting With String.Format MethodString Formatting With f-string MethodData Structures-Creation of ListReaching List Elements – Indexing and SlicingAdding & Modifying & Deleting Elements of ListAdding and Deleting Elements to List with MethodsAdding and Deleting by Index in ListOther List MethodsCreation of TupleReaching Tuple Elements Indexing And SlicingData Structures-Creation of DictionaryReaching Dictionary ElementsAdding & Changing & Deleting Elements in DictionaryDictionary MethodsData Structures-Creation of SetAdding & Removing Elements Methods in SetsDifference Operation Methods In SetsIntersection & Union Methods In SetsAsking Questions to Sets with MethodsInput FunctionsStructure of “if” StatementsStructure of “if-else” StatementsStructure of “if-elif-else” StatementsStructure of Nested “if-elif-else” StatementsCoordinated Programming with “IF” and “INPUT”Ternary ConditionFor Loop in PythonUsing Conditional Expressions and For Loop TogetherList ComprehensionWhile Loop in PythonBreak & Continue CommandMeeting with FunctionsReturn Expression in FunctionsWrite Docstring in FunctionUsing Functions and Conditional Expressions TogetherArguments and ParametersBuilt-in Functions - 1Built-in Functions - 2With my up-to-date course, you will have a chance to keep yourself up-to-date and equip yourself with a range of Python programming skills. I am also happy to tell you that I will be constantly available to support your learning and answer questions.Do not forget ! Python for beginners has the second largest number of job postings relative to all other languages. So it will earn you a lot of money and will bring a great change in your resume.Why would you want to take this course?Our answer is simple: The quality of teaching.When you enroll, you will feel the OAK Academy`s seasoned developers' expertise. What is python?Machine learning python is a general-purpose, object-oriented, high-level programming language. Whether you work in artificial intelligence or finance or are pursuing a career in web development or data science, Python bootcamp is one of the most important skills you can learn. Python's simple syntax is especially suited for desktop, web, and business applications. Python's design philosophy emphasizes readability and usability. Python was developed on the premise that there should be only one way (and preferably, one obvious way) to do things, a philosophy that resulted in a strict level of code standardization. The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing different tools for programmers suited for a variety of tasks.Python vs. R: What is the Difference?Python and R are two of today's most popular programming tools. When deciding between Python and R in data science , you need to think about your specific needs. On one hand, Python is relatively easy for beginners to learn, is applicable across many disciplines, has a strict syntax that will help you become a better coder, and is fast to process large datasets. On the other hand, R has over 10,000 packages for data manipulation, is capable of easily making publication-quality graphics, boasts superior capability for statistical modeling, and is more widely used in academia, healthcare, and finance.What does it mean that Python is object-oriented?Python is a multi-paradigm language, which means that it supports many data analysis programming approaches. Along with procedural and functional programming styles, Python also supports the object-oriented style of programming. In object-oriented programming, a developer completes a programming project by creating Python objects in code that represent objects in the actual world. These objects can contain both the data and functionality of the real-world object. To generate an object in Python you need a class. You can think of a class as a template. You create the template once, and then use the template to create as many objects as you need. Python classes have attributes to represent data and methods that add functionality. A class representing a car may have attributes like color, speed, and seats and methods like driving, steering, and stopping.What are the limitations of Python?Python is a widely used, general-purpose programming language, but it has some limitations. Because Python in machine learning is an interpreted, dynamically typed language, it is slow compared to a compiled, statically typed language like C. Therefore, Python is useful when speed is not that important. Python's dynamic type system also makes it use more memory than some other programming languages, so it is not suited to memory-intensive applications. The Python virtual engine that runs Python code runs single-threaded, making concurrency another limitation of the programming language. Though Python is popular for some types of game development, its higher memory and CPU usage limits its usage for high-quality 3D game development. That being said, computer hardware is getting better and better, and the speed and memory limitations of Python are getting less and less relevant.How is Python used?Python is a general programming language used widely across many industries and platforms. One common use of Python is scripting, which means automating tasks in the background. Many of the scripts that ship with Linux operating systems are Python scripts. Python is also a popular language for machine learning, data analytics, data visualization, and data science because its simple syntax makes it easy to quickly build real applications. You can use Python to create desktop applications. Many developers use it to write Linux desktop applications, and it is also an excellent choice for web and game development. Python web frameworks like Flask and Django are a popular choice for developing web applications. Recently, Python is also being used as a language for mobile development via the Kivy third-party library.What jobs use Python?Python is a popular language that is used across many industries and in many programming disciplines. DevOps engineers use Python to script website and server deployments. Web developers use Python to build web applications, usually with one of Python's popular web frameworks like Flask or Django. Data scientists and data analysts use Python to build machine learning models, generate data visualizations, and analyze big data. Financial advisors and quants (quantitative analysts) use Python to predict the market and manage money. Data journalists use Python to sort through information and create stories. Machine learning engineers use Python to develop neural networks and artificial intelligent systems.How do I learn Python on my own?Python has a simple syntax that makes it an excellent programming language for a beginner to learn. To learn Python on your own, you first must become familiar with the syntax. But you only need to know a little bit about Python syntax to get started writing real code; you will pick up the rest as you go. Depending on the purpose of using it, you can then find a good Python tutorial, book, or course that will teach you the programming language by building a complete application that fits your goals. If you want to develop games, then learn Python game development. If you're going to build web applications, you can find many courses that can teach you that, too. Udemy’s online courses are a great place to start if you want to learn Python on your own.Video and Audio Production QualityAll our videos are created/produced as high-quality video and audio to provide you the best learning experience.You will be,Seeing clearlyHearing clearlyMoving through the course without distractionsYou'll also get:Lifetime Access to The CourseFast & Friendly Support in the Q&A sectionUdemy Certificate of Completion Ready for DownloadDive in now!We offer full support, answering any questions.See you in the " Python | Python Programming Language Course Without Coding " course.Python - Learn Python Programming Language Basics without coding with educational, short lectures & quizzes in a fun way

Overview

Section 1: Python Introduction

Lecture 1 Lecture - 1

Lecture 2 Lecture - 2

Section 2: First Step to Coding

Lecture 3 Lecture - 3

Lecture 4 Lecture - 4

Lecture 5 Lecture - 5

Section 3: Using Quotation Marks in Python Coding

Lecture 6 Lecture - 6

Lecture 7 Lecture - 7

Section 4: Introduction to Basic Data Structures in Python

Lecture 8 Lecture - 8

Lecture 9 Lecture - 9

Lecture 10 Lecture - 10

Section 5: Performing Assignment to Variables

Lecture 11 Lecture - 11

Lecture 12 Lecture - 12

Section 6: Performing Complex Assignment to Variables

Lecture 13 Lecture - 13

Section 7: Type Conversions

Lecture 14 Lecture - 14

Lecture 15 Lecture - 15

Section 8: Arithmetic Operations in Python

Lecture 16 Lecture - 16

Lecture 17 Lecture - 17

Lecture 18 Lecture - 18

Lecture 19 Lecture - 19

Section 9: Examining the Print Function in Depth

Lecture 20 Lecture - 20

Lecture 21 Lecture - 21

Lecture 22 Lecture - 22

Lecture 23 Lecture - 23

Section 10: Escape Sequence Operations

Lecture 24 Lecture - 24

Lecture 25 Lecture - 25

Lecture 26 Lecture - 26

Lecture 27 Lecture - 27

Section 11: Boolean Logic Expressions

Lecture 28 Lecture - 28

Lecture 29 Lecture - 29

Lecture 30 Lecture - 30

Section 12: Examining Strings Specifically

Lecture 31 Lecture - 31

Lecture 32 Lecture - 32

Lecture 33 Lecture - 33

Section 13: Methods in Strings-1

Lecture 34 Lecture - 34

Lecture 35 Lecture - 35

Lecture 36 Lecture - 36

Lecture 37 Lecture - 37

Lecture 38 Lecture - 38

Lecture 39 Lecture - 39

Section 14: Methods in Strings-2

Lecture 40 Lecture - 40

Lecture 41 Lecture - 41

Lecture 42 Lecture - 42

Lecture 43 Lecture - 43

Section 15: Methods in Strings-3

Lecture 44 Lecture - 44

Lecture 45 Lecture - 45

Lecture 46 Lecture - 46

Lecture 47 Lecture - 47

Section 16: Indexing and Slicing in Strings

Lecture 48 Lecture - 48

Lecture 49 Lecture - 49

Lecture 50 Lecture - 50

Lecture 51 Lecture - 51

Section 17: Complex Indexing and Slicing Operations

Lecture 52 Lecture - 52

Lecture 53 Lecture - 53

Section 18: String Formatting with Arithmetic Operations

Lecture 54 Lecture - 54

Section 19: String Formatting With % Operator

Lecture 55 Lecture - 55

Lecture 56 Lecture - 56

Lecture 57 Lecture - 57

Lecture 58 Lecture - 58

Lecture 59 Lecture - 59

Lecture 60 Lecture - 60

Section 20: String Formatting With String.Format Method

Lecture 61 Lecture - 61

Lecture 62 Lecture - 62

Section 21: String Formatting With f-string Method

Lecture 63 Lecture - 63

Section 22: Data Structures- Creation of Lists

Lecture 64 Lecture - 64

Lecture 65 Lecture - 65

Lecture 66 Lecture - 66

Lecture 67 Lecture - 67

Section 23: Reaching List Elements – Indexing and Slicing

Lecture 68 Lecture - 68

Lecture 69 Lecture - 69

Lecture 70 Lecture - 70

Section 24: Adding & Modifying & Deleting Elements of Lists

Lecture 71 Lecture - 71

Lecture 72 Lecture - 72

Section 25: Adding and Deleting Elements to List with Methods

Lecture 73 Lecture - 73

Lecture 74 Lecture - 74

Section 26: Adding and Deleting Elements by Index in List

Lecture 75 Lecture - 75

Lecture 76 Lecture - 76

Section 27: Other List Methods

Lecture 77 Lecture - 77

Section 28: Data Structures – Creation of Tuple

Lecture 78 Lecture - 78

Lecture 79 Lecture - 79

Lecture 80 Lecture - 80

Section 29: Reaching Tuple Elements: Indexing and Slicing

Lecture 81 Lecture - 81

Lecture 82 Lecture - 82

Section 30: Data Structures – Creation of Dictionary

Lecture 83 Lecture - 83

Lecture 84 Lecture - 84

Lecture 85 Lecture - 85

Lecture 86 Lecture - 86

Lecture 87 Lecture - 87

Section 31: Reaching Dictionary Elements

Lecture 88 Lecture - 88

Section 32: Adding & Changing & Deleting Elements in Dictionary

Lecture 89 Lecture - 89

Lecture 90 Lecture - 90

Section 33: Dictionary Methods

Lecture 91 Lecture - 91

Section 34: Data Structures – Creation of Set

Lecture 92 Lecture - 92

Lecture 93 Lecture - 93

Section 35: Adding & Removing Elements Methods in Sets

Lecture 94 Lecture - 94

Lecture 95 Lecture - 95

Section 36: Intersection & Union Methods In Sets

Lecture 96 Lecture - 96

Lecture 97 Lecture - 97

Section 37: Asking Questions to Sets with Methods.

Lecture 98 Lecture - 98

Section 38: Comparison Operators

Lecture 99 Lecture - 99

Lecture 100 Lecture - 100

Lecture 101 Lecture - 101

Lecture 102 Lecture - 102

Section 39: Input Function

Lecture 103 Lecture - 103

Lecture 104 Lecture - 104

Section 40: Structure of “if” Statements

Lecture 105 Lecture - 105

Section 41: Structure of “if-else” Statements

Lecture 106 Lecture - 106

Section 42: Structure of “if-elif-else” Statements

Lecture 107 Lecture - 107

Section 43: Structure of Nested “if-elif-else” Statements

Lecture 108 Lecture - 108

Lecture 109 Lecture - 109

Section 44: Ternary Condition

Lecture 110 Lecture - 110

Lecture 111 Lecture - 111

Section 45: "For" Loops in Python

Lecture 112 Lecture - 112

Lecture 113 Lecture - 113

Lecture 114 Lecture - 114

Section 46: Using Conditional Expressions and For Loop Together

Lecture 115 Lecture - 115

Section 47: List Comprehension

Lecture 116 Lecture - 116

Lecture 117 Lecture - 117

Section 48: Loops - While Loops in Python

Lecture 118 Lecture - 118

Lecture 119 Lecture - 119

Lecture 120 Lecture - 120

Section 49: Break & Continue Command

Lecture 121 Lecture - 121

Lecture 122 Lecture - 122

Section 50: Meeting with Functions

Lecture 123 Lecture - 123

Lecture 124 Lecture - 124

Lecture 125 Lecture - 125

Lecture 126 Lecture - 126

Lecture 127 Lecture - 127

Section 51: Return Expression in Functions

Lecture 128 Lecture - 128

Lecture 129 Lecture - 129

Section 52: Writing Docstring in Functions

Lecture 130 Lecture - 130

Section 53: Using Functions and Conditional Expressions Together

Lecture 131 Lecture - 131

Section 54: Arguments and Parameters

Lecture 132 Lecture - 132

Lecture 133 Lecture - 133

Lecture 134 Lecture - 134

Lecture 135 Lecture - 135

Lecture 136 Lecture - 136

Lecture 137 Lecture - 137

Lecture 138 Lecture - 138

Section 55: Built-In Functions - 1

Lecture 139 Lecture - 139

Lecture 140 Lecture - 140

Lecture 141 Lecture - 141

Lecture 142 Lecture - 142

Lecture 143 Lecture - 143

Lecture 144 Lecture - 144

Lecture 145 Lecture - 145

Section 56: Built-In Functions - 2

Lecture 146 Lecture - 146

Lecture 147 Lecture - 147

Lecture 148 Lecture - 148

Lecture 149 Lecture - 149

Lecture 150 Lecture - 150

Lecture 151 Lecture - 151

Lecture 152 Lecture - 152

Lecture 153 Lecture - 153

Lecture 154 Lecture - 154

Lecture 155 Lecture - 155

Section 57: Extra

Lecture 156 Python | Python Programming Language Course Without Coding

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