The Complete Python Course 2024 by Chris Haroun

The Complete Python Course 2024
Published 3/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz

The most COMPREHENSIVE + UP TO DATE Python Course. Free 980 page book version of course included +Python in Excel +Mojo

What you’ll learn

Learn Python from scratch. There are 4 tracks depending on how much experience the student has with programming.

Go from absolute beginner to expert in this comprehensive course.

Learn NEW Python coding features that were just introduced; this is the MOST UP TO DATE Python course on the market.

Also included is the next generation Python language (Mojo), how to use Python in Excel and much more.

A free 980 page book version of the course is included and is only available to students that take this course.

Learn Python Math (Meaning Operators) and "Strings"

Learn Python Built in Functions & Creating Basic Functions

Learn Python’s List Data Type and the Sum Function

Learn Python Logic and Loops

Learn Python Tuples, Dictionaries and Sets

Learn Python Methods and Advanced Strings

Learn Python Object Oriented Programming (OOP) & Classes

Learn Python NumPy (Numerical Python)

Learn Python Pandas and Polars

Learn Python Data Processing and ETL (Extract, Transform and Load)

Learn Python Writing Clean and Efficient Code Processes

Learn Python in Excel

Learn Mojo

Learn All Built-In Python Functions

Requirements

No programming experience is required to take this course.

Description

Overview

Section 1: Intro, How to Take the Course, Access Free Python Book & Our First Exercise

Lecture 1 Welcome, How to Take the Course and How to Download the Free Python Book

Lecture 2 Introduction to Python (What, Why and How of Level 1)

Lecture 3 How to Use Python Online Using Google Colab for Free

Lecture 4 Exercise 1.1: Our First Python Code: “Hello World”

Lecture 5 Answer 1.1: Our first Python Code: “Hello World”

Lecture 6 Optional Lecture: Who Uses Python & What are the Pros & Cons of Python?

Lecture 9 Exercise 2.1: Using String and Integer Data Types

Lecture 10 Answer 2.1: Using String and Integer Data Types

Lecture 11 Floating and Boolean Data Types

Lecture 12 Exercise 2.2: Using Floating and Boolean Data Types

Lecture 13 Answer 2.2: Using Floating and Boolean Data Types

Lecture 17 Level 2 Final Exercise: Currency Converter

Lecture 18 Level 2 Final Exercise Answer: Currency Converter

Section 3: Level 3: Python Math (Meaning Operators) and "Strings"

Lecture 19 Intro to Python Math (Operators) & Strings (What, Why & How of Level 3)

Lecture 20 Arithmetic Rules in Python

Lecture 21 Exercise 3.1: Arithmetic Rules in Python

Lecture 22 Answer 3.1: Arithmetic Rules in Python

Lecture 26 Level 3 Final Exercise: Simple Interest Calculator for a Savings Account

Lecture 27 Level 3 Final Exercise Answer

Section 4: Level 4: Built in Functions & Creating Basic Functions

Lecture 28 Intro to Built-In/Creating Functions (What, Why & How of Level 4)

Lecture 29 Basic Built in Python Functions that Use Math

Lecture 30 Exercise 4.1: Built in Functions that Use Math

Lecture 31 Answer 4.1: Built in Functions that Use Math

Lecture 32 Input Built in Python Function

Lecture 33 Exercise 4.2: Input Built in Python Function

Lecture 34 Answer 4.2: Input Built in Python Function & Stringing Together Objects

Lecture 41 Creating Advanced Functions (Keyword and Default Values)

Lecture 42 Exercise 4.5: Creating Advanced Functions Keyword and Default Values)

Lecture 43 Answer 4.5: Creating Advanced Functions (Keyword and Default Values)

Lecture 44 Returning Values from Custom Functions

Lecture 45 Exercise 4.6: Returning Values from Custom Functions

Lecture 46 Answer 4.6: Returning Values from Custom Functions

Lecture 47 Level 4 Final Exercise: Simple Calculator with Functions

Lecture 48 Level 4 Final Exercise Answer: Simple Calculator with Functions

Section 5: Level 5: The List Data Type and the Sum Function

Lecture 49 Intro to List Data Type (What, Why and How of Level 5)

Lecture 50 How Does the List Data Type Work (and Using the SUM Function)?

Lecture 51 Exercise 5.1: The List Data Type Work (and Using the SUM Function)

Lecture 52 Answer 5.1: The List Data Type Work (and Using the SUM Function)

Lecture 53 Level 5 Final Exercise: Grocery Shopping List

Lecture 54 Level 5 Final Exercise Answer: Grocery Shopping List

Section 6: Level 6: Logic and Loops

Lecture 55 Intro to Logic and Loops (What, Why and How of Level 6)

Lecture 56 The IF, ELSE Statement

Lecture 57 Exercise 6.1: The IF, ELSE Statement

Lecture 58 Answer 6.1: The IF, ELSE Statement

Lecture 59 Using A Nested IF Statement

Lecture 60 Exercise 6.2: Using A Nested IF Statement

Lecture 61 Answer 6.2: Using A Nested IF Statement

Lecture 62 Using ELIF in an IF Statement and the OR & AND Logic

Lecture 63 Exercise 6.3: Using ELIF in an IF Statement and the OR & AND Logic

Lecture 64 Answer 6.3: Using ELIF in an IF Statement and the OR & AND Logic

Lecture 65 Using the MATCH and CASE Logic

Lecture 66 Exercise 6.4: Using the MATCH and CASE Logic

Lecture 67 Answer 6.4: Using the MATCH and CASE Logic

Lecture 68 Formatting

Lecture 69 Exercise 6.5: Formatting

Lecture 70 Answer 6.5: Formatting

Lecture 71 Slicing

Lecture 72 Exercise 6.6: Slicing

Lecture 73 Answer 6.6: Slicing

Lecture 74 For Loop

Lecture 75 Exercise 6.7: For Loop

Lecture 76 Answer 6.7: For Loop

Lecture 77 While Loop

Lecture 78 Exercise 6.8: While Loop

Lecture 79 Answer 6.8: While Loop

Lecture 80 Level 6 Final Exercise: Time Tracker for Tasks

Lecture 81 Level 6 Final Exercise Answer: Time Tracker for Tasks

Section 7: Level 7: 3 More Data Types: Tuple, Dictionary and Set

Lecture 82 Intro to More Data Types (What, Why and How of Level 7)

Lecture 83 Tuples Explained How is it Different from a List?

Lecture 84 Exercise 7.1: Tuples

Lecture 85 Answer 7.1: Tuples

Lecture 86 Introduction to Dictionaries

Lecture 87 Dictionary Methods/Functionality

Lecture 88 Exercise 7.2: Dictionaries

Lecture 89 Answer 7.2: Dictionaries

Lecture 90 Introduction to Sets

Lecture 91 Exercise 7.3: Sets

Lecture 92 Answer 7.3: Sets

Lecture 93 Level 7 Final Exercise: Restaurant Menu Manager

Lecture 94 Level 7 Final Exercise Answer: Restaurant Menu Manager

Section 8: Level 8: Methods and Advanced Strings

Lecture 95 Intro to Methods and Advanced Strings (What, Why and How of Level 8)

Lecture 96 What is a Method and How do Get the Methods for An Object?

Lecture 97 Exercise 8.1: Methods

Lecture 98 Answer 8.1: Methods

Lecture 99 String Methods

Lecture 100 Exercise 8.2: String Methods

Lecture 101 Answer 8.2: String Methods

Lecture 102 Advanced String Operations

Lecture 103 Exercise 8.3: Advanced String Operations

Lecture 104 Answer 8.3: Advanced String Operations

Lecture 105 [G/A] Lambda Functions & Map

Lecture 106 [G/A] Recursion

Lecture 107 Level 8 Final Exercise: Customer Support Chat Log Analysis

Lecture 108 Level 8 Final Exercise Answer: Customer Support Chat Log Analysis

Section 9: Level 9: Object Oriented Programming (OOP) & Classes

Lecture 109 Intro to OOP (What, Why and How of Level 9)

Lecture 110 Understanding Classes and Instances

Lecture 111 Exercise 9.1: Creating Your First Class and Instance

Lecture 112 Answer 9.1: Creating Your First Class and Instance

Lecture 113 Defining Methods in a Class

Lecture 114 Understanding Self in Python

Lecture 115 Class Attributes Versus Instance Attributes

Lecture 116 Exercise 9.2: Classes, Instances and Attributes

Lecture 117 Answer 9.2: Classes, Instances and Attributes

Lecture 118 Inheritance: Extending Functionality

Lecture 119 Encapsulation: Hiding Information

Lecture 120 Exercise 9.3: Implementing Encapsulation

Lecture 121 Answer 9.3: Implementing Encapsulation

Lecture 122 Understanding Magic Dunder Methods

Lecture 123 [G/A] Understanding Composition and Aggregation

Lecture 124 [G/A] Level 9 Final Exercise: Simple Bank Account Manager

Lecture 125 [G/A] Level 9 Final Exercise Answer: Simple Bank Account Manager

Section 10: Level 10 Mastering NumPy (Numerical Python)

Lecture 126 Intro to NumPy (What, Why and How of Level 10)

Lecture 127 Libraries Explained and Installing NumPy

Lecture 128 Arrays Data Type

Lecture 129 NumPy Array Creation Methods

Lecture 130 Operations with Arrays

Lecture 131 Slicing NumPy Arrays

Lecture 132 Exercise/Project 10.1: Slicing and Indexing with NumPy

Lecture 133 Answer 10.1: Slicing and Indexing with NumPy

Lecture 134 Loops Versus Vectorization

Lecture 135 Exercise/Project 10.2: Vectorization

Lecture 136 Answer 10.2: Vectorization

Lecture 137 Universal Functions

Lecture 138 Conditional Filtering

Lecture 139 Reshaping Arrays

Lecture 140 Handling Missing Values Using NumPy

Lecture 141 File Handling

Section 11: Level 11: Pandas and Polars

Lecture 142 Intro to Pandas & Polars (What, Why and How of Level 11)

Lecture 143 Installing Pandas and Polars

Lecture 144 Loading Data Using Pandas and Polars

Lecture 145 Reading Data in Different Ways

Lecture 146 Exercise 11.1: First Pandas/Polars Exercise

Lecture 147 Answer 11.1: First Pandas/Polars Exercise

Lecture 148 Understanding Series

Lecture 149 Dataframe Operations

Lecture 150 Dealing with Missing Data

Lecture 151 Map and Transform

Lecture 152 Merging and Joining

Lecture 153 Exercise 11.2: Second Pandas/Polars Exercise

Lecture 154 Answer 11.2: Second Pandas/Polars Exercise

Lecture 155 Strings

Lecture 156 Sales Data Visualization

Lecture 157 Exercise 11.3: Third Pandas/Polars Exercise

Lecture 158 Answer 11.3: Third Pandas/Polars Exercise

Section 12: Level 12: Data Processing and ETL (Extract, Transform and Load)

Lecture 159 Intro to Data Processing and ETL (What, Why and How of Level 12)

Lecture 165 Handling Imbalanced Data

Section 13: Level 13: Writing Clean and Efficient Code

Lecture 167 Intro to Writing Clean/Efficient Code (What, Why and How of Level 13)

Lecture 168 Clean and Modular Code

Lecture 169 Python Naming Conventions

Lecture 170 Documentation

Lecture 171 Testing Your Code

Lecture 172 Working with Teams on GitHub

Lecture 173 Questionnaire on How to Conduct a Code Review

Section 14: Level 14: Using Python in Excel

Lecture 174 Introduction to Using Python in Excel (What, Why and How of Level 14)

Lecture 175 How to Install Python In Excel

Lecture 176 How to Use Python In Excel

Lecture 177 Exercise 14.1: Using Python in Excel

Lecture 178 Answer 14.1: Using Python in Excel

Lecture 179 Using Dataframes with Python in Excel

Lecture 180 Exercise 14.2: Using Python Dataframes in Excel

Lecture 181 Answer 14.2: Using Python Dataframes in Excel

Lecture 182 How to Create a Linear Regression Using Python In Excel

Lecture 183 Exercise 14.3: Using Python and Excel to Create a Regression Analysis

Lecture 184 Answer 14.3: Using Python and Excel to Create a Regression Analysis

Section 15: [G/A] Level 15: Mojo

Lecture 185 [G/A] Intro to Mojo (What, Why and How of Level 15)

Lecture 186 [G/A] What is Mojo and Why is it a Gamer Changer for Python Developers?

Lecture 187 [G/A] Complied Versus Interpreted Programming When it Comes to Mojo

Lecture 188 [G/A] Coding with Mojo

Lecture 190 [G/A] Data Types in Mojo

Lecture 191 [G/A] Else If in Mojo

Lecture 192 [G/A] Loops in Mojo

Lecture 193 [G/A] Functions in Mojo

Lecture 194 [G/A] Struct Versus Class In Mojo

Lecture 195 [G/A] Error Handling in Mojo

Lecture 196 [G/A] "Inout, Borrowed and Owned" in Mojo

Lecture 197 [G/A] Importing NumPy in Mojo

Section 16: Level 16: All Built-In Python Functions

Lecture 198 Intro to All Built-In Python Functions (What, Why and How of Level 16)

Lecture 199 Absolute Value Built-In Function: abs( )

Lecture 200 All Built-In Function: all( )

Lecture 201 Any Built-In Function: any( )

Lecture 202 [G/A] ASCII Built-In Function: ascii ( )

Lecture 203 [G/A] Bin Built-In Function: bin( )

Lecture 204 Bool Built-In Function: bool( )

Lecture 205 Breakpoint Built-In Function: breakpoint( )

Lecture 206 [G/A] Bytearray Built-In Function: bytearray( )

Lecture 207 [G/A] Bytes Built-In Function: bytes( )

Lecture 208 Callable Built-In Function: callable( )

Lecture 209 Chr Built-In Function: chr ( )

Lecture 210 Classmethod Built-In Function: classmethod( )

Lecture 211 [G/A] Compile Built-In Function: compile( )

Lecture 212 [G/A] Complex Built-In Function: complex( )

Lecture 213 Dict Built-In Function: dict( )

Lecture 214 Dir Built-In Function: dir( )

Lecture 215 Divmod Built-In Function: divmod( )

Lecture 216 [G/A] Enumerate Built-In Function: enumerate( )

Lecture 217 Eval Built-In Function: eval( )

Lecture 218 Exec Built-In Function: exec( )

Lecture 219 Filter Built-In Function: filter( )

Lecture 220 Float Built-In Function: float( )

Lecture 221 Format Built-In Function: format( )

Lecture 222 Frozenset Built-In Function: frozenset( )

Lecture 223 Hash Built-In Function: hash( )

Lecture 224 Help Built-In Function: help( )

Lecture 225 Hex Built-In Function: hex( )

Lecture 226 ID Built-In Function: id( )

Lecture 227 Input Built-In Function: input( )

Lecture 228 Int Built-In Function: int( )

Lecture 229 [G/A] Isinstance Built-In Function: isinstance( )

Lecture 230 Issubclass Built-In Function: issubclass( )

Lecture 231 Iter Built-In Function: iter( )

Lecture 232 Len Built-In Function: len( )

Lecture 233 List Built-In Function: list( )

Lecture 234 [G/A] Map Built-In Function: map( )

Lecture 235 Max Built-In Function: Max( )

Lecture 236 Min Built-In Function: Min( )

Lecture 237 Next Built-In Function: next( )

Lecture 238 [G/A] Oct Built-In Function: oct( )

Lecture 239 Open Built-In Function: open( )

Lecture 240 S16L43 Ord Built-In Function: ord( )

Lecture 241 Pow Built-In Function: pow( )

Lecture 242 Print Built-In Function: print( )

Lecture 243 Range Built-In Function: range( )

Lecture 244 Repr Built-In Function: repr( )

Lecture 245 Reversed Built-In Function: reversed( )

Lecture 246 Round Built-In Function: round( )

Lecture 247 Set Built-In Function: set( )

Lecture 248 Slice Built-In Function: slice( )

Lecture 249 Sorted Built-In Function: sorted( )

Lecture 250 Str Built-In Function: str( )

Lecture 251 Sum Built-In Function: sum( )

Lecture 252 Tuple Built-In Function: tuple( )

Lecture 253 Type Built-In Function: type( )

Lecture 254 Zip Built-In Function: zip( )

Section 17: Level 17: Conclusion, Next Steps and Additional Python Topics

Lecture 255 CONGRATULATIONS & Next Steps!

Section 18: Bonus Materials

Lecture 256 Bonus Items

This course is for anyone interested in learning beginner, intermediate or advanced Python skills (no programming experience is required).[/b][/i][/b]