Python Programming - Beginner to Professional Python Programming

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• Python Course Intro 51:11

  • 1: Intro To Python Programming 05:20
  • 2: What is Python Programming 09:30
  • 3: Who is This Course For 04:33
  • 4: Python Marketplace 05:46
  • 5: Python Job Opportunities 04:43
  • 6: Python Job Roles 08:41
  • 7: Python Course Structure 04:18
  • 8: Getting a python job w.o degree 08:20

• Getting Familiar With Python 1:14:05

  • 9: Getting Familiar With Python (section overview) 05:56
  • 10: Installing Python on Windows 09:36
  • 11: Anaconda and Jupyter Notebooks 07:30
  • 12: Anaconda and Jupyter Notebooks 2 16:24
  • 13: Comments 05:01
  • 14: Python Syntax 02:13
  • 15: Line Structure 02:43
  • 16: Line Structure 07:11
  • 17: Joining Lines 05:00
  • 18: Multiple Statements on a Single Line 04:52
  • 19: Indentation 07:39

• Python Data Types 1:29:27

  • 20: Python Basic Data Types (section overview) 08:25
  • 21: Strings Overview 09:50
  • 22: String Manipulation 07:17
  • 23: String Indexing 04:28
  • 24: String Slicing 08:16
  • 25: Printing 09:48
  • 26: Python Variables 08:09
  • 27: Integers and Float 08:26
  • 28: Booleans 04:53
  • 29: Mini-Project 1 Letter Counter (1) 19:55

• Python Operators 52:35

  • 30: Python Operators (section overview) 04:11
  • 31: Comparison Operators 09:20
  • 32: Arithmetic Operators 08:17
  • 33: Assignment Operators 03:40
  • 34: Logical Operators 12:36
  • 35: Identity Operators (Need slide update as (Equality is misspelled) 04:41
  • 36: Membership Operators 02:01
  • 37: Bitwise Operators 07:49

• Python Advanced Data Types 45:55

  • 38: Python Advanced Data Types (section overview) 10:37
  • 39: Sets 06:01
  • 40: List Overview 04:38
  • 41: List Indexing and Slicing 04:25
  • 42: Tuples 02:20
  • 43: Dictionary 10:40
  • 44: When to use each one 04:31
  • 45: Compound Data Types 02:43

• Python Control Flow 1 56:14

  • 46: Control Flow Part 1 (section overview) 15:00
  • 47: For Loops 09:50
  • 48: Intro to Control Flow 00:56
  • 49: Basic Conditional Statements 13:38
  • 50: More Conditional Statements 05:04
  • 51: While Loops 11:46

• Python Control Flow 2 31:03

  • 52: Control Flow Part 2 (section overview) 02:28
  • 53: Break Statements 07:59
  • 54: Continue Statements 04:51
  • 55: Zip Function 07:20
  • 56: Enumerate Function 03:58
  • 57: List Comprehension 04:27

• Intro to Functions 29:41

  • 58: Python Functions (section overview) 02:49
  • 59: Intro to Functions 02:16
  • 60: Python Help Function 03:11
  • 61: Defining Functions 09:29
  • 62: Variable Scope 08:12
  • 63: DocStrings 03:44

• User Input and Error Handling 41:05

  • 64: Error Handling and User Input (section overview) 01:48
  • 65: Intro to Error Handling 02:48
  • 66: User Input 04:21
  • 67: Syntax Errors 04:00
  • 68: Exceptions 11:22
  • 69: Handling Exceptions 1 08:29
  • 70: Handling Exceptions 2 08:17

• Advanced Functions 1:03:12

  • 71: Python Advanced Functions (section overview) 05:10
  • 72: Lambda Functions 05:29
  • 73: Functions args and kwargs 10:01
  • 74: Iterators 08:12
  • 75: Generators and Yield 11:53
  • 76: Map Functions 14:24
  • 77: Filter 08:03

• Scripting and Libraries 1:07:39

  • 78: Scripting and Libraries (section overview) 04:29
  • 79: What is a script. 01:24
  • 80: What is an IDE 17:20
  • 81: What is a text editor 11:46
  • 82: from jupyter notebook to vscode 1 14:45
  • 83: From jupyter notebook to vscode 2 05:03
  • 84: Importing Scripts 03:04
  • 85: Standard Libraries 04:13
  • 86: Third Party Libraries 05:35

• NumPy 58:06

  • 87: Numpy section overview 04:07
  • 88: What is NumPy 04:28
  • 89: Why NumPy 04:09
  • 90: NumPy Arrays 10:23
  • 91: Reshaping, Modifying and Accessing NumPy arrays 07:19
  • 92: Slicing and Copying 05:52
  • 93: Inserting , Deleting, Appending 09:45
  • 94: Logical Indexing 03:43
  • 95: Broadcasting 08:20

• Pandas 1:30:20

  • 96: Pandas 16:43
  • 97: Pandas Series 16:58
  • 98: Pandas DataFrame 17:04
  • 99: Pandas DataFrame Manipulation 12:54
  • 100: Dealing with Missing Values 10:09
  • 101: Pandas Series Manipulation 16:32

• Intro To OOP 41:01

  • 102: Functional vs OOP 06:16
  • 103: OOP key defintions 04:04
  • 104: Create your First Class 12:09
  • 105: How to create and use Objects 06:04
  • 106: Modifying Attributes 12:28

• Advanced OOP 1:14:07

  • 107: Python Decorators 27:09
  • 108: Property Decorator 08:43
  • 109: Class Methods Decorator 07:11
  • 110: Static Methods Decorators 10:28
  • 111: Inheritance 20:36

• Career in Python 1:04:22

  • 112: Starting a Career in Python Overview 05:55
  • 113: Getting Started with Freelancing 09:26
  • 114: Building a Brand 11:56
  • 115: Personal Branding 13:08
  • 116: Importance of Website Blog 04:22
  • 117: Networking Dos Don ts 05:31
  • 118: Top Freelance Sites 08:04
  • 119: Creating a Python Developer Resume 06:00

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With the help and knowledge of industry leaders, the original Python Programming - Beginner to Professional Python Programming was created. This Python Programming - Beginner to Professional Python Programming has been meticulously created to suit all of the learning criteria for making a significant contribution to the associated subject and subsequent career path. By participating in this Python Programming - Beginner to Professional Python Programming course, the student will receive valuable knowledge and skills that will help them land their ideal career and establish a strong personal and professional reputation.

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Curriculum

Course Curriculum: Python Programming - Beginner to Professional Python Programming

Here is a curriculum breakdown of the Python Programming - Beginner to Professional Python Programming course:

1 - Python Course Intro

1 - Intro To Python Programming

2 - What is Python Programming

3 - Who is This Course For

4 - Python Marketplace

5 - Python Job Opportunities

6 - Python Job Roles

7 - Python Course Structure

8 - Getting a python job w.o degree

2 - Getting Familiar With Python

9 - Getting Familiar With Python (section overview)

10 - Installing Python on Windows

11 - Anaconda and Jupyter Notebooks 1

12 - Anaconda and Jupyter Notebooks 2

13 - Comments

14 - Python Syntax

15 - Line Structure

16 - Line Structure

17 - Joining Lines

18 - Multiple Statements on a Single Line

19 - Indentation

3 - Python Data Types

20 - Python Basic Data Types (section overview)9

21 - Strings Overview

22 - String Manipulation

23 - String Indexing

24 - String Slicing

25 - Printing

26 - Python Variables

27 - Integers and Float

28 - Booleans

29 - Mini-Project 1 Letter Counter (1)

4 - Python Operators

30 - Python Operators (section overview)

31 - Comparison Operators

32 - Arithmetic Operators

33 - Assignment Operators

34 - Logical Operators

35 - Identity Operators (Need slide update as (Equality is misspelled)

36 - Membership Operators

37 - Bitwise Operators

5 - Python Advanced Data Types

38 - Python Advanced Data Types (section overview)

39 - Sets

40 - List Overview

41 - List Indexing and Slicing

42 - Tuples

43 - Dictionary

44 - When to use each one

45 - Compound Data Types

6 - Python Control Flow 1

46 - Control Flow Part 1 (section overview)

47 - For Loops

48 - Intro to Control Flow

49 - Basic Conditional Statements

50 - More Conditional Statements

51 - While Loops

7 - Python Control Flow 2

52 - Control Flow Part 2 (section overview)

53 - Break Statements

54 - Continue Statements

55 - Zip Function

56 - Enumerate Function

57 - List Comprehension

8 - Intro to Functions

58 - Python Functions (section overview)

59 - Intro to Functions

60 - Python Help Function

61 - Defining Functions

62 - Variable Scope

63 - DocStrings

9 - User Input and Error Handling

64 - Error Handling and User Input (section overview)

65 - Intro to Error Handling

66 - User Input

67 - Syntax Errors

68 - Exceptions

69 - Handling Exceptions

70 - Handling Exceptions

10 - Advanced Functions

71 - Python Advanced Functions (section overview)

72 - Lambda Functions

73 - Functions args and kwargs

74 - Iterators

75 - Generators and Yield

76 - Map Functions

77 - Filter

11 - Scripting and Libraries

78 - Scripting and Libraries (section overview)

79 - What is a script.

80 - What is an IDE

81 - What is a text editor

82 - from jupyter notebook to vscode

83 - From jupyter notebook to vscode

84 - Importing Scripts

85 - Standard Libraries

86 - Third Party Libraries

12 - NumPy

87 - Numpy section overview

88 - What is NumPy

89 - Why NumPy

90 - NumPy Arrays

91 - Reshaping, Modifying and Accessing NumPy arrays

92 - Slicing and Copying

93 - Inserting , Deleting, Appending

94 - Logical Indexing

95 - Broadcasting

13 - Pandas

96 - Pandas

97 - Pandas Series

98 - Pandas DataFrame

99 - Pandas DataFrame Manipulation

100 - Dealing with Missing Values

101 - Pandas Series Manipulation

14 - Intro To OOP

102 - Functional vs OOP

103 - OOP key defintions

104 - Create your First Class

105 - How to create and use Objects

106 - Modifying Attributes

15 - Advanced OOP

107 - Python Decorators

108 - Property Decorator

109 - Class Methods Decorator

110 - Static Methods Decorators

111 - Inheritance

16 - Career in Python

112 - Starting a Career in Python Overview

113 - Getting Started with Freelancing

114 - Building a Brand

115 - Personal Branding

116 - Importance of Website Blog

117 - Networking Dos Don ts

118 - Top Freelance Sites

119 - Creating a Python Developer Resume

The Python Programming - Beginner to Professional Python Programming training course is ideal for highly driven students who wish to improve your personal and professional abilities while also preparing for the career of their dreams! This Python Programming - Beginner to Professional Python Programming is also great for persons who want to learn more about this topic in depth and appreciate being up to speed on the newest facts and expertise.

• There are no official requirements for Python Programming - Beginner to Professional Python Programming
• Python Programming - Beginner to Professional Python Programming requires a basic Internet connection
• Python Programming - Beginner to Professional Python Programming requires you to have access to a computer, tablet, or a mobile device
• Knowledge of basic English

The Python Programming - Beginner to Professional Python Programming course is meant to prepare you for the job of your dreams, a promotion at work, or being self-employed and starting your own business.

Courses from the Academy of Skills will help you enhance your profession and keep your skills current.

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