Mosh Hamedani – Complete Python Mastery
Description ADD UP TO $ 30K TO YOUR SALARY FOR MASTER PYTHON! Python is the most popular programming language in the world. The average salary for a Python developer is $ 116k in the United States. 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 for its simple and elegant syntax. It is 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 a long description! Find out how to use Python in automation, web development, and machine learning. BY THE END OF THIS COURSE, YOU WILL BE ABLE TO … Write Python code with confidence Get ready to learn web development and machine learning with Python Create command line utilities Automate boring and repetitive tasks Write clean code like a pro WHAT YOU LEARN … Along with all the fundamentals of programming, you will learn how … Use essential Python data structures Use classes and modules Apply object-oriented programming principles Work with exceptions Build web scraping tools Use third-party Python packages and publish your own Work with files and directories Work with CSV, JSON, Excel spreadsheets, PDF, ZIP files, etc. Send emails and text messages Automate UI testing with Selenium Call back end API Basics of building web applications with Python and Django Using Python in Machine Learning and Data Science Projects And a lot lot more! WHO IS THIS COURSE FOR? Anyone who wants to learn programming for the first time College students who want to understand Python better 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 Curriculum Course 1- Introduction (32m) Start1- What is Python (3:21) Start2- Python Installation (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- Python code execution (2:59) Start10- Python Implementations (2:28) Start11- How Python code is executed (2:46) Start12- Quiz (1:37)
2- Primitive types (34m) Home1- Variables (3:04) Start2- Variable names (3:02) Home3- Strings (5:30) Start4- Escape Sequences (2:40) Start5- Formatted Strings (2:08) Start6- String Methods (5:54) Home7- Numbers (2:46) Start8- Working with Numbers (2:09) Start9- Type conversion (5:04) Home10- Quiz (2:43) 3- Flow control (37m) Start1- Comparison Operators (2:04) Start2- Conditional Statements (4:09) Start3- Ternary operator (2:09) Start4- Logical Operators (4:02) Home5- Short Circuit Evaluation (2:06) Start6- Chaining Comparison Operators (1:22) Start7- Quiz (1:43) Start8- For Loops (3:38) Start9 – Stop … More (2:46) Home10- Nested Loops (2:44) Start11- Iterable (3:08) Home12- While Loops (4:59) Home13- infinite loops (1:37) Start14- Exercise (2:05) 4- Functions (41m) Start1- Defining functions (2:24) Home2- 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- Reach (5:09) Start9- Debugging (6:50) Start10- VSCode Coding Tricks – Windows (2:21) Start11- VSCode Coding Tricks – Mac (1:49) Start12- Exercise (1:29) Home13- Solution (4:41) StartA Quick note 5- Data structures (1h20m) Home1- Lists (3:54) Start2- Access to elements (3:13) Start3- Unpacking List (3:51) Start4- Looping over lists (2:54) Home5- Add or remove items (2:56) Start6- Find Articles (1:28) Start7- Leaderboards (4:35) Start8- Lambda Functions (1:49) Start9- Map function (3:25) Start10- Filter function (2:05) Start11- Comprehension List (3:10) Start12- Zip function (1:49) Home13- Batteries (4:24) Start14- Queues (2:50) Home15- Tuples (4:02) Start16- Variable exchange (2:37) Home17- Matrices (3:11) Home18- Sets (4:03) Home19- Dictionaries (5:24) Start20- Comprehension Dictionary (3:19) Start21- Expression Generator (3:51) Start22- Unpacking Operator (4:05) Start23- Exercise (6:21) 6- Exceptions (20m) Start1- Exceptions (2:16) Start2- Exceptions Handling (4:10) Start3- Handling different exceptions (3:05) Start4- Cleaning (1:57) Home5- The Declaration With (3:07) Start6- Increase in exceptions (3:21) Home7- Cost of increasing 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- Object comparison (3:11) Start8- Performing arithmetic operations (1:31) Start9- Custom Container Manufacturing (6:55) Start10- Private Members (3:40) Home11- Properties (7:30) Start12- Inheritance (4:23) Start13- The object class (2:23) Start14- Method override (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- Typing Duck (2:50) Start21- Extension of built-in types (2:26) Start22- Data classes (4:36) 8- Modules (20m) Start1- Creation of modules (4:16) Start2- Python compiled 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- Execution of modules as scripts (2:55)9- Python standard library (1h) Start1- Python Standard Library (0:51) Start2- Work with paths (4:48) Start3- Work with directories (4:14) Start4- Work with files (3:59) Start5- Work with Zip files (3:15) Start6- Work with CSV files (4:50) Start7- Work with JSON files (3:57) Start8- Work with a SQLite database (9:10) Home9- Working with timestamps (2:24) Start10- Work with DateTimes (5:05) Start11- Working with Time Deltas (2:41) Start12- Generation of random values (4:09) Start13- Open the browser (1:12) Start14- Sending emails (6:48) Home15- Templates (4:53) Start16- Command Line Arguments (1:54) Start17- Execution of 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) Home6- Pipfile (4:48) Start7- Dependency Management (3:28) Start8- Publish 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) Home3- Yelp API (2:51) Start4- Search for companies (9:54) Start5- Hide API Keys (2:05) Start6- Sending text messages (6:02) Data encoding method 🙂 Start8- Browser automation (11:28) Home9- Working with PDF files (6:18) Start10- Work with Excel spreadsheets (9:52) Start11- Principle of separation of command queries (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 application (3:41) Data encoding method 🙂 Start5- Models (4:57) Start6- Migrations (8:00) Home7- Changing the models (5:38) Home8- Administration (4:29) Home9- Administrator Customization (6:55) Start10- Database Abstraction API (3:52) Home11- Templates (10:23) Start12- Adding Bootstrap (4:19) Start13- Design customization (2:23) Start14- Share a template across multiple applications (3:48) Start15- Url Parameters (4:37) Start16- Get a single object (3:48) Home17- Increase in 404 errors (3:51) Start18- Reference addresses (3:47) Start19- API Creation (9:26) Start20- Add the home page (4:27) Start21- Preparing to implement (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 dataset (6:21) Start5- Jupyter Shortcuts (5:26) Start6- A real machine learning problem (3:17) Start7- Data preparation (3:05) Start8- Learning and Prediction (4:04) Home9- Calculation of precision (6:20) Start10- Persistent Models (3:14) Start11- Visualization of a decision tree (6:26) Start12- What to learn next Start13 – Thank you
tristian –
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