Published 1/2023MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHzLanguage: English | Size: 3.77 GB | Duration: 5h 12m

A hands-on guide to learning Python programming language

What you'll learn

Understand the basic concepts of programming and computer science, including data types, variables, control structures, and algorithms.

Be able to write and run simple Python programs using the command line or a programming environment like IDLE.

Understand how to use Python to manipulate and analyze data, including reading and writing files, working with lists and dictionaries, and using modules and lib

Be able to use Python's built-in functions and modules to perform common tasks, such as reading and writing files, handling exceptions, and working with dates a

Understand how to use control structures in Python, including if/else statements, for loops, and while loops.

Understand how to define and use functions in Python, including arguments, return values, and scoping.

Understand how to use Python's object-oriented features, including classes, inheritance, and polymorphism.

Be able to use Python's built-in debugging tools, such as the debugger and the traceback module, to troubleshoot and fix errors in your code.

Understand how to use Python's built-in testing tools, such as the unittest module, to write and run automated tests for your code.

Understand how to use Python's built-in documentation tools, such as docstrings and the pydoc module, to document your code and make it easier for others to und

Be able to use Python's built-in features to solve real-world problems and build useful applications.

Requirements

No prior programming experience is required, but it may be helpful if you have some basic problem-solving skills and are comfortable with math and logical reasoning.

A computer: You will need a computer with an operating system that can run Python. Most modern computers should be able to run Python, but you may need to install it first.

A text editor or programming environment: You will need a way to write and edit your Python code. There are many options available, rag from simple text editors like Notepad or TextEdit to more advanced programming environments like IDLE or PyCharm.

Basic computer skills: It will be helpful if you are comfortable using a computer and are familiar with basic concepts like navigating the file system and using the command line (if you are using a text editor).

Description

Welcome to "Learn with Python" the ultimate guide to mastering the Python programming language. With our highly efficient and effective teaching method, you'll become a proficient Python programmer in record . Our comprehensive coverage of advanced Python concepts will set you apart in the job market and give you the skills and confidence you need to succeed.Throughout this course, you'll gain practical skills and knowledge that you can immediately apply to real-world projects and tasks. You'll join a thriving community of Python learners and get access to ongoing support and resources to help you on your learning journey. Our interactive exercises and quizzes will reinforce key concepts and help you improve your problem-solving skills and critical thinking.With clear and concise explanations, you'll get a comprehensive understanding of Python programming. Our real-world examples and hands-on projects will maximize your productivity and help you apply your new skills immediately. By the end of this course, you'll be a sought-after Python programmer with the expertise and confidence you need to advance your career.Join us on the path to Python mastery with "Learn with Python".Course Contents:Setting up the environment with Jupyter Notebook with PythonA simple Introduction to Python with PythonCreate a calculator with Python with Python 3.1. Numbers with Python 3.2. Strings with Python3.3. Lists with Python 3.4. First Steps Towards Programming with PythonControl Flow Tools with Python 4.1. if Statements with Python 4.2. for Statements with Python 4.3. The range Function with Python 4.4. break and continue Statements, and else Clauses on Loops with Python 4.5. pass Statements with Python Defining Functions with Python 5.1. More on Defining Functions with Python5.2 Default Argument Values with Python 4.7.2. Keyword Arguments with Python 4.7.3. Special parameters with Python 4.7.3.1. Positional-or-Keyword Arguments with Python 4.7.3.2. Positional-Only Parameters with Python4.7.3.3. Keyword-Only Arguments with Python 4.7.3.4. Function Examples with Python4.7.3.5. Recap with Python4.7.4. Arbitrary Argument Lists with Python 4.7.5. Unpacking Argument Lists with Python 4.7.6. Lambda Expressions with Python 4.7.7. Documentation Strings with Python 4.7.8. Function Annotations with Python 4.8. Intermezzo: Coding Style with Python5. Data Structures with Python 5.1. More on Lists with Python 5.1.1. Using Lists as Stacks with Python 5.1.2. Using Lists as Queues with Python 5.1.3. List Comprehensions with Python 5.1.4. Nested List Comprehensions with Python 5.2. The del statement with Python 5.3. Tuples and Sequences with Python 5.4. Sets with Python 5.5. Dictionaries with Python 5.6. Looping Techniques with Python 5.7. More on Conditions with Python 5.8. Comparing Sequences and Other Types with PythonModules with Python 6.1. More on Modules with Python 6.1.1. Executing modules as scripts with Python 6.1.2. The Module Search Path with Python 6.1.3. “Compiled” Python files with Python6.2. Standard Modules with Python 6.3. The dir Function with Python 6.4. Packages with Python 6.4.1. Importing * From a Package with Python 6.4.2. Intra-package References with Python 6.4.3. Packages in Multiple Directories with PythonInput and Output with Python 7.1. Fancier Output Formatting with Python 7.1.1. Formatted String Literals with Python 7.1.2. The String format Method with Python 7.1.3. Manual String Formatting with Python 7.1.4. Old string formatting with Python 7.2. Reading and Writing Files with Python 7.2.1. Methods of File Objects with Python 7.2.2. Saving structured data with json with Python 8. Errors and Exceptions with Python 8.1. Syntax Errors with Python 8.2. Exceptions with Python 8.3. Handling Exceptions with Python 8.4. Raising Exceptions with Python 8.5. Exception Chaining with Python 8.6. User-defined Exceptions with Python 8.7. Defining Clean-up Actions with Python 8.8. Predefined Clean-up Actions with PythonClasses with Python 9.1. A Word About Names and Objects with Python 9.2. Python Scopes and Namespaces with Python9.2.1. Scopes and Namespaces Example with Python 9.3. A First Look at Classes with Python 9.3.1. Class Definition Syntax with Python 9.3.2. Class Objects with Python 9.3.3. Instance Objects with Python 9.3.4. Method Objects with Python 9.3.5. Class and Instance Variables with Python 9.4. Random Remarks with Python 9.5. Inheritance with Python 9.5.1. Multiple Inheritance with Python 9.6. Private Variables with Python 9.7. Odds and Ends with Python 9.8. Iterators with Python 9.9. Generators with Python 9.10. Generator Expressions with PythonThe Standard Library with Python 10.1. Operating System Interface with Python 10.2. File Wildcards with Python 10.3. Command Line Arguments with Python 10.4. Error Output Redirection and Program Teation with Python 10.5. String Pattern Matching with Python 10.6. Mathematics with Python 10.7. Internet Access with Python 10.8. Dates and s with Python 10.9. Data Compression with Python 10.10. Performance Measurement with Python 10.11. Quality Control with Python 10.12. Batteries Included with PythonOutput Formatting with Python 11.2. Templating with Python 11.3. Working with Binary Data Record Layouts with Python 11.4. Multi-threading with Python 11.5. Logging with Python 11.6. Weak References with Python 11.7. Tools for Working with Lists with Python 11.8. Decimal Floating Point Arithmetic with PythonVirtual Environments and Packages with Python 12.1. Introduction to Packages with Python 12.2. Importing Packages with Python 12.3. The Module Search Path with Python 12.4. Packages in Multiple Directories with Python 12.5. Package Data with Python 12.6. Installing Packages with Python 12.7. Requirements Files with Python 12.8. Virtual Environments with Python

Overview

Section 1: Introduction with Python

Lecture 1 Introduction with Python

Section 2: Getting Started with Python

Lecture 2 Getting Started with Python

Lecture 3 Numbers with Python

Lecture 4 Strings with Python

Lecture 5 Lists with Python

Section 3: Control Flow Tools with Python

Lecture 6 If Statements with Python

Lecture 7 for Statements with Python

Lecture 8 The range Function with Python

Lecture 9 pass Statements

Lecture 10 break and continue Statements, and else Clauses on Loops

Section 4: Functions with Python

Lecture 11 Functions with Python

Lecture 12 Keyword Arguments with Python

Lecture 13 Special Parameters with Python

Lecture 14 Arbitrary Argument List with Python

Lecture 15 Unpacking Argyment Lists with Python

Lecture 16 Lambda Expressions with Python

Lecture 17 Documentation Strings with Python

Lecture 18 Function Annotations with Python

Lecture 19 Coding Style with Python

Section 5: Data Structures with Python

Lecture 20 Advanced Lists with Python

Lecture 21 Stacks with Python

Lecture 22 Queues with Python

Lecture 23 List Comprehensions with Python

Lecture 24 Nested Lists with Python

Lecture 25 The del Statement with Python

Lecture 26 Tuples & Sets with Python

Lecture 27 Dictionaries with Python

Lecture 28 Looping & Conditions Techniques with Python

Section 6: Modules with Python

Lecture 29 Modules with Python

Lecture 30 Standard Modules with Python

Lecture 31 Packages with Python

Section 7: Input & Output with Python

Lecture 32 Output Formatting with Python

Lecture 33 Formatted String Literals with Python

Lecture 34 The String format Method with Python

Lecture 35 Manual String Formatting with Python

Lecture 36 Old String Formatting with Python

Lecture 37 Reading & Writing Files with Python

Lecture 38 Files with Python

Lecture 39 JSON with Python

Section 8: Errors and Exceptions

Lecture 40 Errors with Python

Lecture 41 Exceptions with Python

Lecture 42 Handling Exceptions with Python

Lecture 43 Exception Chaining with Python

Lecture 44 User-defined Exceptions with Python

Lecture 45 Defining Clean-up Actions with Python

Section 9: Classes with Python

Lecture 46 Scopes & Namespaces with Python

Lecture 47 Classes with Python

Lecture 48 Instance Objects with Python

Lecture 49 Variables & Methods with Python

Lecture 50 Empty Class with Python

Lecture 51 Class Example with Python

Lecture 52 Inheritance with Python

Lecture 53 Private Variables with Python

Lecture 54 Iterators with Python

Lecture 55 Generators with Python

Lecture 56 Generator Expressions with Python

Section 10: The Standard Library with Python

Lecture 57 Operating System with Python

Lecture 58 Command Line with Python

Lecture 59 Regex with Python

Lecture 60 Math with Python

Lecture 61 Internet with Python

Lecture 62 Dates & s with Python

Lecture 63 Compression with Python

Lecture 64 Performance with Python

Lecture 65 QA & Test with Python

Lecture 66 More on Output Formatting with Python

Lecture 67 Templating with Python

Lecture 68 Multi Threading with Python

Lecture 69 Logging with Python

Lecture 70 Arrays with Python

Lecture 71 Decimal Floating Point with Python

Section 11: Virtual Environments with Python

Lecture 72 Virtual Environments with Python

Lecture 73 pip with Python

Section 12: Wrap up and what’s coming next with Python

Lecture 74 Wrap up and what’s coming next with Python

Python is a good choice for anyone who is interested in learning to program, whether you want to build web applications, analyze data, create games, or something else entirely. If you are motivated to learn and are willing to put in some and effort, you can learn Python and use it to achieve your goals.

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