Mosh Hamedani – Complete Python Mastery | Available Now !

Mosh Hamedani – Complete Python Mastery | Instant Download !

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Add up to $30k to your salary by mastering Python!

Python is the most popular programming language in the world. The average salary for a Python developer is $116k in the USA. That’s almost $30k more than other developers!

Python is used by big companies like Google, Facebook, Dropbox, Reddit, Spotify, Quora, etc.

Mathematicians, scientists, engineers and developers love it because of its simple and elegant syntax.

It’s the #1 language for AI and machine learning, and the ideal language to learn for beginners. Much easier than C++ or JavaScript!

This course teaches you everything Python has to offer from the basics to more advanced topics.

A perfect mix of theory and practice, packed with real-world examples, exercises and step-by-step solutions – free of “fluff” and lengthy description!

Discover how to use Python in automation, web development and machine learning.

By the end of this course, you’ll be able to…

• Write Python code with confidence
• Get ready to learn web development and machine learning with Python
• Build command-line utilities
• Automate boring, repetitive tasks

Write clean code like a pro

What You’l Learn…

Along with all the programming fundamentals, you’ll learn how to…

• Use essential Python data structures
• Use classes and modules
• Apply object-oriented programming principles
• Work with exceptions
• Build web scraping tools
• Use 3rd-party Python packages and publish your own
• Work with files and directories
• Work with CSV, JSON, Excel spreadsheets, PDFs, ZIP files, etc
• Send emails and text messages
• Automate UI testing with Selenium
• Call backend APIs
• Basics of building web apps with Python and Django
• Use Python in machine learning and data science projects

And much, much more!

Who is this course for?

• Anyone who wants to learn programming for the first time
• College students who want to better understand Python
• Anyone who wants to automate repetitive tasks with Python
• Anyone pursuing a career in AI, data science or web development
• Python developers who want to brush up on their Python skills

Course Curriculum

1- Getting Started (32m)
Start1- What is Python (3:21)
Start2- Installing Python (1:52)
Start3- Python Interpreter (1:55)
Start4- Code Editors (1:19)
Start5- Your First Python Program (3:36)
Start6- Python Extension (2:52)
Start7- Linting Python Code (4:14)
Start8- Formatting Python Code (3:54)
Start9- Running Python Code (2:59)
Start10- Python Implementations (2:28)
Start11- How Python Code is Executed (2:46)
Start12- Quiz (1:37)
2- Primitive Types (34m)
Start1- Variables (3:04)
Start2- Variable Names (3:02)
Start3- Strings (5:30)
Start4- Escape Sequences (2:40)
Start5- Formatted Strings (2:08)
Start6- String Methods (5:54)
Start7- Numbers (2:46)
Start8- Working with Numbers (2:09)
Start9- Type Conversion (5:04)
Start10- Quiz (2:43)
3- Control Flow (37m)
Start1- Comparison Operators (2:04)
Start2- Conditional Statements (4:09)
Start3- Ternary Operator (2:09)
Start4- Logical Operators (4:02)
Start5- Short-circuit Evaluation (2:06)
Start6- Chaining Comparison Operators (1:22)
Start7- Quiz (1:43)
Start8- For Loops (3:38)
Start9- For..Else (2:46)
Start10- Nested Loops (2:44)
Start11- Iterables (3:08)
Start12- While Loops (4:59)
Start13- Infinite Loops (1:37)
Start14- Exercise (2:05)
4- Functions (41m)
Start1- Defining Functions (2:24)
Start2- Arguments (2:20)
Start3- Types of Functions (4:02)
Start4- Keyword Arguments (2:00)
Start5- Default Arguments (1:35)
Start6- xargs (4:15)
Start7- xxargs (2:20)
Start8- Scope (5:09)
Start9- Debugging (6:50)
Start10- VSCode Coding Tricks – Windows (2:21)
Start11- VSCode Coding Tricks – Mac (1:49)
Start12- Exercise (1:29)
Start13- Solution (4:41)
StartA Quick Note
5- Data Structures (1h20m)
Start1- Lists (3:54)
Start2- Accessing Items (3:13)
Start3- List Unpacking (3:51)
Start4- Looping over Lists (2:54)
Start5- Adding or Removing Items (2:56)
Start6- Finding Items (1:28)
Start7- Sorting Lists (4:35)
Start8- Lambda Functions (1:49)
Start9- Map Function (3:25)
Start10- Filter Function (2:05)
Start11- List Comprehensions (3:10)
Start12- Zip Function (1:49)
Start13- Stacks (4:24)
Start14- Queues (2:50)
Start15- Tuples (4:02)
Start16- Swapping Variables (2:37)
Start17- Arrays (3:11)
Start18- Sets (4:03)
Start19- Dictionaries (5:24)
Start20- Dictionary Comprehensions (3:19)
Start21- Generator Expressions (3:51)
Start22- Unpacking Operator (4:05)
Start23- Exercise (6:21)
6- Exceptions (20m)
Start1- Exceptions (2:16)
Start2- Handling Exceptions (4:10)
Start3- Handling Different Exceptions (3:05)
Start4- Cleaning Up (1:57)
Start5- The With Statement (3:07)
Start6- Raising Exceptions (3:21)
Start7- Cost of Raising Exceptions (4:41)
7- Classes (1h25m)
Start1- Classes (2:35)
Start2- Creating Classes (3:45)
Start3- Constructors (4:37)
Start4- Class vs Instance Attributes (3:58)
Start5- Class vs Instance Methods (4:05)
Start6- Magic Methods (3:13)
Start7- Comparing Objects (3:11)
Start8- Performing Arithmetic Operations (1:31)
Start9- Making Custom Containers (6:55)
Start10- Private Members (3:40)
Start11- Properties (7:30)
Start12- Inheritance (4:23)
Start13- The Object Class (2:23)
Start14- Method Overriding (3:14)
Start15- Multi-level Inheritance (2:42)
Start16- Multiple Inheritance (3:22)
Start17- A Good Example of Inheritance (4:31)
Start18- Abstract Base Classes (4:50)
Start19- Polymorphism (3:56)
Start20- Duck Typing (2:50)
Start21- Extending Built-in Types (2:26)
Start22- Data Classes (4:36)
8- Modules (20m)
Start1- Creating Modules (4:16)
Start2- Compiled Python Files (2:19)
Start3- Module Search Path (1:35)
Start4- Packages (2:27)
Start5- Sub-packages (1:01)
Start6- Intra-package References (1:36)
Start7- The dir Function (1:39)
Start8- Executing Modules as Scripts (2:55)
9- Python Standard Library (1h)
Start1- Python Standard Library (0:51)
Start2- Working With Paths (4:48)
Start3- Working with Directories (4:14)
Start4- Working with Files (3:59)
Start5- Working with Zip Files (3:15)
Start6- Working with CSV Files (4:50)
Start7- Working with JSON Files (3:57)
Start8- Working with a SQLite Database (9:10)
Start9- Working with Timestamps (2:24)
Start10- Working with DateTimes (5:05)
Start11- Working with Time Deltas (2:41)
Start12- Generating Random Values (4:09)
Start13- Opening the Browser (1:12)
Start14- Sending Emails (6:48)
Start15- Templates (4:53)
Start16- Command-line Arguments (1:54)
Start17- Running External Programs (8:06)
10- Python Package Index (1h30m)
Start1- Pypi (1:49)
Start2- Pip (6:23)
Start3- Virtual Environments (4:04)
Start4- Pipenv (3:40)
Start5- Virtual Environments in VSCode (3:49)
Start6- Pipfile (4:48)
Start7- Managing Dependencies (3:28)
Start8- Publishing Packages (8:22)
Start9- Docstrings (5:48)
Start10- Pydoc (4:06)
11- Popular Python Packages (1h30m)
Start1- Introduction (1:41)
Start2- What are APIs (2:36)
Start3- Yelp API (2:51)
Start4- Searching for Businesses (9:54)
Start5- Hiding API Keys (2:05)
Start6- Sending Text Messages (6:02)
Start7- Web Scraping (9:06)
Start8- Browser Automation (11:28)
Start9- Working with PDFs (6:18)
Start10- Working with Excel Spreadsheets (9:52)
Start11- Command Query Separation Principle (4:39)
Start12- NumPy (9:05)
12- Building Web Applications with Django (30m)
Start1- Introduction (1:43)
Start2- Your First Django Project (4:11)
Start3- Your First App (3:41)
Start4- Views (7:59)
Start5- Models (4:57)
Start6- Migrations (8:00)
Start7- Changing the Models (5:38)
Start8- Admin (4:29)
Start9- Customizing the Admin (6:55)
Start10- Database Abstraction API (3:52)
Start11- Templates (10:23)
Start12- Adding Bootstrap (4:19)
Start13- Customizing the Layout (2:23)
Start14- Sharing a Template Across Multiple Apps (3:48)
Start15- Url Parameters (4:37)
Start16- Getting a Single Object (3:48)
Start17- Raising 404 Errors (3:51)
Start18- Referencing Urls (3:47)
Start19- Creating APIs (9:26)
Start20- Adding the Homepage (4:27)
Start21- Getting Ready to Deploy (9:44)
Start22- Deployment (7:59)
Machine Learning with Python (30m)
Start1- What is Machine Learning (1:58)
Start2- Machine Learning in Action (2:47)
Start3- Libraries and Tools (4:54)
Start4- Importing a Data Set (6:21)
Start5- Jupyter Shortcuts (5:26)
Start6- A Real Machine Learning Problem (3:17)
Start7- Preparing the Data (3:05)
Start8- Learning and Predicting (4:04)
Start9- Calculating the Accuracy (6:20)
Start10- Persisting Models (3:14)
Start11- Visualizing a Decision Tree (6:26)
Start12- What to Learn Next
Start13- Thank You