What will i learn?
- Have a fundamental understanding of the Python programming language.
- Acquire the pre-requisite Python skills to move into specific branches - Machine Learning, Data Science, etc..
- Understand how to create your own Python programs.
- Have the skills and understanding of Python to confidently apply for Python programming jobs.
- Add the Python Object-Oriented Programming (OOP) skills to your résumé.
Curriculum for this course
154 Lessons
44:31:07 Hours
Introdution
1 Lessons
00:18:09 Hours
- Course Overview 00:18:09
A Quick Refresher - Basics Review
10 Lessons
02:23:06 Hours
- Introduction 00:01:44
- The Python Type Hierarchy 00:05:52
- Multi-Line Statements and Strings 00:21:50
- Variable Names 00:11:01
- Conditionals 00:07:39
- Functions 00:12:28
- The While Loop 00:14:26
- Break, Continue and the Try Statement 00:10:26
- The For Loop 00:17:22
- Classes 00:40:18
Variables and Memory
14 Lessons
03:02:06 Hours
- Introduction 00:02:55
- Variables are Memory References 00:08:22
- Reference Counting 00:14:22
- Garbage Collection 00:26:40
- Dynamic vs Static Typing 00:05:29
- Variable Re-Assignment 00:04:49
- Object Mutability 00:15:23
- Function Arguments and Mutability 00:17:30
- Shared References and Mutability 00:09:37
- Variable Equality 00:14:23
- Everything is an Object 00:13:59
- Python Optimizations Interning 00:09:15
- Python Optimizations String Interning 00:19:12
- Python Optimizations Peephole 00:20:10
Numeric Types
32 Lessons
07:58:05 Hours
- Introduction 00:02:59
- Integers Data Types 00:18:08
- Integers Operations 00:24:26
- Integers Constructors and Bases - Lecture 00:29:35
- Integers Constructors and Bases - Coding 00:20:24
- Rational Numbers - Lecture 00:14:28
- Rationals Numbers - Coding 00:12:34
- Floats Internal Representations - Lecture 00:19:53
- Floats Internal Representations - Coding 00:04:57
- Floats Equality Testing - Lecture 00:18:43
- Floats Equality Testing - Coding 00:14:41
- Floats Coercing to Integers - Lecture 00:09:40
- Floats Coercing to Integers - Coding 00:05:04
- Floats Rounding - Lecture 00:25:23
- Floats Rounding - Coding 00:13:34
- Decimals - Lecture 00:16:50
- Decimals - Coding 00:10:28
- Decimals Constructors and Contexts - Lecture 00:10:07
- Decimals Constructors and Contexts - Coding 00:10:29
- Decimals Math Operations - Lecture 00:09:33
- Decimals Math Operations - Coding 00:13:31
- Decimals Performance Considerations 00:10:30
- Complex Numbers - Lecture 00:11:29
- Complex Numbers - Coding 00:14:17
- Booleans 00:21:01
- Booleans Truth Values - Lecture 00:09:09
- Booleans Truth Values - Coding 00:14:48
- Booleans Precedence and Short-Circuiting - Lecture 00:21:11
- Booleans Precedence and Short-Circuiting - Coding 00:13:39
- Booleans Boolean Operators - Lecture 00:14:46
- Booleans Boolean Operators - Coding 00:20:54
- Comparison Operators 00:20:54
Function Parameters
16 Lessons
03:53:13 Hours
- Introduction 00:01:06
- Argument vs Parameter 00:03:44
- Positional and Keyword Arguments - Lecture 00:13:06
- Unpacking Iterables - Lecture 00:13:02
- Unpacking Iterables - Coding 00:21:10
- Extended Unpacking - Lecture 00:17:51
- Extended Unpacking - Coding 00:29:05
- args - Coding 00:11:48
- Keyword Arguments - Lecture 00:09:24
- Keyword Arguments - Coding 00:14:19
- kwargs 00:10:29
- Putting it all Together - Lecture 00:13:26
- Putting it all Together - Coding 00:17:26
- Application A Simple Function Timer 00:19:09
- Parameter Defaults - Beware!! 00:18:45
- Parameter Defaults - Beware Again!! 00:19:23
First-Class Functions
18 Lessons
05:19:16 Hours
- Introduction 00:04:06
- Docstrings and Annotations - Lecture 00:15:59
- Docstrings and Annotations - Coding 00:15:03
- Lambda Expressions - Lecture 00:12:11
- Lambda Expressions - Coding 00:15:00
- Lambdas and Sorting 00:15:57
- Challenge - Randomize an Iterable using Sorted!! 00:02:56
- Function Introspection - Lecture 00:19:31
- Function Introspection - Coding 00:28:37
- Callables 00:14:47
- Map, Filter, Zip and List Comprehensions - Lecture 00:21:44
- Map, Filter, Zip and List Comprehensions - Coding 00:21:15
- Reducing Functions - Lecture 00:25:53
- Reducing Functions - Coding 00:21:11
- Partial Functions - Lecture 00:11:13
- Partial Functions - Coding 00:25:33
- The operator Module - Lecture 00:15:36
- The operator Module - Coding 00:32:44
Scopes, Closures and Decorators
21 Lessons
08:34:44 Hours
- Introduction 00:01:32
- Global and Local Scopes - Lecture 00:34:55
- Global and Local Scopes - Coding 00:15:41
- Nonlocal Scopes - Lecture 00:22:18
- Nonlocal Scopes - Coding 00:14:38
- Closures - Lecture 00:38:36
- Closures - Coding 00:32:06
- Closure Applications - Part 1 00:15:39
- Closure Applications - Part 2 00:18:41
- Decorators (Part 1) - Lecture 00:21:07
- Decorators (Part 1) - Coding 00:21:00
- Decorator Application (Timer) 00:35:17
- Decorator Application (Logger, Stacked Decorators) 00:23:48
- Decorator Application (Memoization) 00:29:15
- Decorators (Part 2) - Lecture 00:11:45
- Decorators (Part 2) - Coding 00:25:58
- Decorator Application (Decorator Class) 00:09:41
- Decorator Application (Decorating Classes) 00:48:24
- Decorator Application (Dispatching) - Part 1 00:31:46
- Decorator Application (Dispatching) - Part 2 00:35:46
- Decorator Application (Dispatching) - Part 3 00:26:51
Tuples as Data Structures and Named Tuples
11 Lessons
03:31:31 Hours
- Introduction 00:03:19
- Tuples as Data Structures - Lecture 00:19:02
- Tuples as Data Structures - Coding 00:25:25
- Named Tuples - Lecture 00:27:50
- Named Tuples - Coding 00:35:15
- Named Tuples - Modifying and Extending - Lecture 00:14:26
- Named Tuples - Modifying and Extending - Coding 00:21:47
- Named Tuples - DocStrings and Default Values - Lecture 00:13:31
- Named Tuples - DocStrings and Default Values - Coding 00:15:47
- Named Tuples - Application - Returning Multiple Values 00:06:23
- Named Tuples - Application - Alternative to Dictionaries 00:28:46
Modules, Packages and Namespaces
16 Lessons
05:43:29 Hours
- Introduction 00:03:02
- What is a Module 00:24:31
- How does Python Import Modules 00:49:33
- Imports and importlib 00:27:40
- Import Variants and Misconceptions - Lecture 00:14:01
- Import Variants and Misconceptions - Coding 00:27:04
- Reloading Modules 00:18:30
- Using __main__ 00:27:02
- Modules Recap 00:13:03
- What are Packages - Lecture 00:20:25
- What are Packages - Coding 00:27:12
- Why Packages 00:13:08
- Structuring Packages - Part 1 00:36:42
- Structuring Packages - Part 2 00:27:28
- Namespace Packages 00:10:39
- Importing from Zip Archives 00:03:29
Extras
15 Lessons
03:47:28 Hours
- Introduction 00:03:41
- Additional Resources 00:12:54
- Python 3.6 Highlights 00:07:50
- Python 3.6 - Dictionary Ordering 00:19:46
- Python 3.6 - Preserved Order of kwargs and Named Tuple Application 00:05:33
- Python 3.6 - Underscores in Numeric Literals 00:03:39
- Python 3.6 - f-Strings 00:09:20
- Random Seeds 00:17:27
- Random Choices 00:26:09
- Random Samples 00:07:03
- Timing code using timeit 00:16:18
- Don't Use args and kwargs Names Blindly 00:07:36
- Command Line Arguments 01:00:08
- Sentinel Values for Parameter Defaults 00:11:03
- Simulating a simple switch in Python 00:19:01
Requirements
- A computer - Windows, Mac, and Linux are all supported. Setup and installation instructions are included for each platform.
- Your enthusiasm to learn this go-to programming language. It’s a valuable lifetime skill which you can’t un-learn!
- Everything else needed to start programming in Python is already included in the course.
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Description
Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse.
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