Published 1/2023
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: 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, ranging 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 time. 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 Termination with Python 10.5. String Pattern Matching with Python 10.6. Mathematics with Python 10.7. Internet Access with Python 10.8. Dates and Times 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 & Times 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 time and effort, you can learn Python and use it to achieve your goals.
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