One Week Python

One Week Python

English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 183 lectures (13h 47m) | 4.68 GB

A Quick and Effective Way To Learn Python, Made For Busy People

Don’t waste your time with 60+ hour behemoth courses that you never finish! Instead, try this quick and effective pathway to Python that was designed with your sanity in mind. This course is the p1erfect first step into the world of data science, web dev, machine learning, or any other discipline that requires Python knowledge.

As an-person coding bootcamp instructor, I created this course to keep you engaged the entire way through. It’s full of exercises, quizzes, challenges, and projects. The slides, diagrams, and cheatsheets were painstakingly designed to help you visualize the tricky concepts. There are no 20-minute monster videos in this course; the average video is only 4 minutes long. Everything about this course has been designed to make it actually completable!

This course covers all the Python essentials you need: everything from variables to data structures to object oriented programming and modules. You’ll fill up your Python toolbox so you can go on and tackle libraries like pandas, flask, scikitlearn, django, and more.

What this course is not: This course is not a complete guide to every single possible feature in the Python language. It focuses on the 80% that is absolutely critical and worth your time, but there are other (much longer) courses that are more akin to Python textbooks that take the time to cover every feature. In fact, I created one of those courses, and it happens to be 40 hours long!

Here’s a detailed breakdown of what we cover:

  • Painless installation for all platforms and users
  • Working with numbers
  • Python variables
  • Strings and string methods
  • Booleans
  • Conditional Logic
  • Boolean Logic
  • Loops
  • Functions
  • Scope
  • Lists
  • Dictionaries
  • Sets
  • Tuples
  • *args and **kwargs
  • Working with errors
  • Custom modules
  • 3rd party modules
  • PIP
  • Object Oriented Programming
  • Classes

What you’ll learn

  • Master modern Python fundamentals as quickly as possible
  • Learn the Python you need to move on to Data Science or Web Development
  • Work with 3rd party Python libraries and modules
  • Complete dozens of exercises, quizzes, and projects
  • You’ll learn to code with Python while staying sane!
Table of Contents

Introduction
1 Welcome To The Course!
2 What This Course IS NOT
3 Why You Should Learn Python
4 What We Can Do With Python

Installation
5 Python Versions They Actually Matter!
6 Ways of Running Python
7 Installation For Mac Users
8 Installation For Windows Users
9 The No-Installation Option REPL.it

Numbers DONE
10 Intro to Data Types
11 Integers and Floats
12 OPTIONAL Numeric Notations
13 Basic Operators
14 Lesser Known Operators

Variables Basics DONE
15 Variables
16 Variable Naming
17 Assignment Operators
18 Numbers & Variables In The Wild
19 ★ Magic Trick Exercise

Strings Basics DONE
20 Introducing Strings
21 String Variables
22 String Operators
23 String Indexing

String Basics II DONE
24 String Slices
25 Print()
26 Escape Characters
27 Triple Quotes
28 Strings In The Wild
29 ★ Nico Hülkenberg Exercise

Strings & Built-Ins DONE
30 Introducing Functions
31 Len
32 Input
33 Type Casting
34 ★ Age Calculator Exercise
35 F Strings
36 F-Strings and Type Casting In The Wild
37 ★ Shopping Cart Exercise

Strings and Methods DONE
38 Introducing Methods Upper and Lower
39 Navigating The Docs
40 Help() & ipython ”
41 Reading Function Signatures + Strip Methods
42 Replace
43 Other String Methods
44 Method Chaining
45 String Methods In The Wild
46 ★ Press Release Exercise
47 What I Didn’t Cover

Booleans DONE
48 Introducing Booleans
49 Comparison Operators
50 Equality Operators
51 Comparing Across Types
52 Truthiness & Falseyness
53 The in Operator
54 OPTIONAL Comparing Strings
55 Booleans In The Wild

Conditionals Basics DONE
56 Introducing Conditionals
57 The If Keyword
58 The Elif Keyword
59 The Else Keyword
60 ★ Name Length Codealong
61 ★ Tweet Checker Exercise

Conditionals Part II DONE
62 A Tangent On Indentation
63 Nesting Conditionals
64 ★ Water Boiling Codealong
65 Conditionals In The Wild
66 ★ Quick 1-Question Feedback Survey
67 ★ BMI Calculator Exercise

Writing More Complex Logic DONE
68 Logical AND
69 Using Logical AND In Practice
70 Logical OR
71 Using Logical OR In Practice
72 Logical NOT
73 Using Logical NOT In Practice

More On Logical Operators DONE
74 TruthyFalsey Testing
75 Logical Operator Precedence
76 Logical Operators In The Wild
77 ★ Rock Paper Scissors Exercise Intro
78 ★ Rock Paper Scissors Exercise

Loops Part I DONE
79 Introducing Loops!
80 While Loops
81 ★ While Loops Practice
82 Avoiding Infinite Loops
83 ★ Snake Eyes Codealong
84 For Loops
85 Loops and Indentation
86 The range() function
87 ★ 99 Bottles Of Beer Codealong
88 ★ Loops Problem Set

Loops Part II DONE
89 Break and Continue Keywords
90 ★ Dice Roller Exercise
91 ★ Dice Roller Exercise Solution
92 Working With Nested Loops
93 Loops In The Wild
94 ★ Toothpick Game Exercise Intro
95 ★ Toothpick Game Exercise
96 ★ Toothpick Game Refactor

Functions
97 Introducing Functions
98 Our Very First Function!
99 Functions With An Input
100 Functions With Multiple Arguments
101 Introducing Return!
102 Using The Return Keyword
103 ★ Function Practice Set
104 Default Parameters
105 Ordering Default Parameters
106 KeywordNamed Arguments

Scope DONE
107 Global Scope
108 Local Scope
109 Scope In Loops and Conditionals
110 Enclosing Scope
111 Built-In Scope
112 Scope Precedence Rules
113 The ‘Global’ Keyword

Lists Basics DONE
114 Creating Lists
115 Accessing Data In Lists
116 Updating List Elements
117 append() and extend()
118 insert()
119 List Slices
120 Deletion Methods pop(), popitems(), remove()
121 Iterating Over Lists
122 Lists + Loops Patterns
123 ★ Grand Prix Exercise

Lists Part 2
124 Nested Lists
125 List Operators
126 Sort(), Reverse(), and Count()
127 Lists Are Mutable
128 Comparing Lists == vs is
129 Join() and Split()
130 List Unpacking
131 Copying Lists
132 ★ Todo List Exercise Intro
133 ★ Todo List Exercise Solution
134 What I Didn’t Cover WIP

Dictionaries
135 Introducing Dictionaries
136 Creating Your Own Dictionaries
137 Accessing Data In Dictionaries
138 Adding and Updating Data In Dictionaries
139 The get() method and in operator
140 Dictionary pop(), clear(), and del
141 Dictionaries Are Mutable Too!
142 Iterating Dicts keys(), values(), and items()
143 Fancy Dictionary Merging
144 Lists and Dicts Combined!
145 ★ Peak Dictionary Exercise
146 What I Didn’t Cover

Sets and Tuples DONE
147 Introducing Tuples
148 Tuple Functionality
149 Why Use Tuples
150 Sets Introduction
151 Working With Sets
152 Set Operators Intersection, Union, Difference
153 When Use Sets

Returning To Functions DONE
154 Introducing args
155 Using args
156 Introducing kwargs
157 Parameter List Ordering
158 A Common Gotcha Mutable Default Args
159 Unpacking Args
160 ★ ArgsKwargs Problem Set

Errors
161 Common Error Types
162 Raising Exceptions
163 When To Raise
164 Try and Except
165 LBYL and EAFP

Modules DONE
166 Working With Built-In Modules
167 Importing More Built-In Modules
168 Fancy Import Syntax
169 Creating Custom Modules
170 rd Party Modules Pip & PyPI
171 Our First Pip Package!
172 Language Translator Package
173 ★ Sentiment Analysis Fun Project Installation
174 ★ Sentiment Analysis Fun Project

OOP
175 Introducing OOP
176 Class Syntax
177 Writing Our First Class
178 Instance Methods
179 Practicing Instance Methods
180 Class Attributes
181 Class Methods
182 Inheritance Basics
183 The super() Function

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