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About Developer

Khamisi Kibet

Khamisi Kibet

Software Developer

I am a computer scientist, software developer, and YouTuber, as well as the developer of this website, spinncode.com. I create content to help others learn and grow in the field of software development.

If you enjoy my work, please consider supporting me on platforms like Patreon or subscribing to my YouTube channel. I am also open to job opportunities and collaborations in software development. Let's build something amazing together!

  • Email

    infor@spinncode.com

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    Nairobi, Kenya
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## Course Objectives - Gain a deep understanding of Python fundamentals and its modern ecosystem. - Learn best practices for writing clean, efficient, and scalable Python code. - Master popular Python libraries and frameworks for data science, web development, and automation. - Develop expertise in version control, testing, packaging, and deploying Python projects. ## Weekly Breakdown ### Week 1: Introduction to Python and Environment Setup #### Topics: - [**Overview of Python: History, popularity, and use cases.**](https://spinncode.com/designs/sBM9848p): Discover the history of Python, from its creation by Guido van Rossum to its current status as a top programming language. Learn about its popularity, real-world applications, and various use cases in web development, data science, machine learning, automation, gaming, and education. Explore how you can unlock opportunities with Python. - [**Setting up a Python development environment (Virtualenv, Pipenv, Conda).**](https://spinncode.com/designs/VYrvyzyQ): Discover how to set up a Python development environment using Virtualenv, Pipenv, or Conda, and learn why isolation, reproducibility, and efficient development are crucial for Python projects. Explore the key differences between these tools and choose the right one for your needs, enabling you to simplify troubleshooting and collaboration. - [**Introduction to Python's package manager (pip) and virtual environments.**](https://spinncode.com/designs/BLiZPR5D): Managing dependencies and isolating environments are crucial for efficient Python development. Learn about pip, Python's package manager, and how to work with virtual environments to streamline your workflow. Create self-contained environments for each project to ensure consistency and reduce errors. - [**Exploring Python's basic syntax: Variables, data types, control structures.**](https://spinncode.com/designs/UiOQqIel): Explore Python's basic syntax and control structures, including variables, data types, conditional statements, and loops, and discover how to apply them in real-world examples. Learn how to store and manipulate data, control the flow of your program, and make informed coding decisions. Mastering these fundamentals is crucial for building a strong foundation in Python programming. #### Lab: - [**Install Python, set up a virtual environment, and write your first Python script.**](https://spinncode.com/designs/XeKkzaFZ) #### Lab Summary: Learn how to install Python, set up a virtual environment, and write your first Python script, with step-by-step instructions and code examples to get you started with Python development. Discover the benefits of using virtual environments and how to manage dependencies for your project. Master the basics of running Python scripts and get ready to dive deeper into Python programming. ### Week 2: Data Structures and Basic Algorithms #### Topics: - [**Understanding Python’s built-in data types: Lists, tuples, dictionaries, sets.**](https://spinncode.com/designs/hXBlAwZr): Discover the fundamentals of Python's built-in data structures, including lists, tuples, dictionaries, and sets, and learn how to create and manipulate them with key methods and operations. Understand the differences between these data types, including mutability, ordering, and memory efficiency, and solidify your understanding with practical exercises. - [**Working with iterators and generators for efficient looping.**](https://spinncode.com/designs/JSK1hD2a): Discover how to work efficiently with large datasets in Python using iterators and generators, and learn how these tools improve performance, scalability, and memory efficiency in your programs. You'll gain hands-on experience with creating custom iterators and generators using real-world examples and understand how to apply them to streamline your code. Take your Python skills to the next level by mastering these essential concepts. - [**Comprehensions (list, dict, set comprehensions) for concise code.**](https://spinncode.com/designs/BZiSWGyh): Learn the fundamentals of Python comprehensions and how to use them to write concise, readable, and efficient code. Discover the different types of comprehensions in Python, including list, dict, and set comprehensions, and how to use conditional statements to filter elements. Mastering comprehensions will take your Python coding skills to the next level. - [**Basic algorithms: Sorting, searching, and common patterns.**](https://spinncode.com/designs/PmKbOEYP): Discover the fundamental algorithms in Python programming, including sorting algorithms like Bubble Sort, Selection Sort, and Insertion Sort, as well as searching algorithms like Linear Search and Binary Search. Learn how to implement these algorithms efficiently and effectively in Python, and explore the built-in sorting and searching algorithms available in the language. #### Lab: - [**Implement data manipulation tasks using lists, dictionaries, and comprehensions.**](https://spinncode.com/designs/r1fgEtbZ) #### Lab Summary: Master the fundamentals of data manipulation in Python using lists, dictionaries, and comprehensions to efficiently store, access, and transform data. Learn essential techniques for working with ordered data in lists, key-value pairs in dictionaries, and concise data creation with comprehensions. ### Week 3: Functions, Modules, and Best Practices #### Topics: - [**Defining and using functions: Arguments, return values, and scope.**](https://spinncode.com/designs/GUUudtly): Discover the power of functions in Python, including how to define and use them, function arguments, return values, scope, and local variables, plus best practices for writing efficient and readable code. Learn to write functions that reduce code duplication, improve reusability, and enhance code readability. Explore expert tips and resources to master Python functions. - [**Understanding Python’s module system and creating reusable code.**](https://spinncode.com/designs/7qEqpPof): Learn the fundamentals of Python's module system, how to create reusable code, and best practices for organizing and importing modules in Python, to write more maintainable and scalable code. Discover how to create modules, import them into other projects, and customize the module search path. - [**Using built-in modules and the Python Standard Library.**](https://spinncode.com/designs/WcsocEsL): Mastering Python's built-in modules and Standard Library can significantly streamline your coding process. Explore commonly used modules like math, random, time, and os, and learn how to use them in your Python code, enabling you to write more efficient and effective programs. - [**Best practices: DRY (Don’t Repeat Yourself), writing clean and readable code (PEP 8).**](https://spinncode.com/designs/c92j1nQY): Write more efficient Python code by applying the Don't Repeat Yourself principle and following PEP 8 guidelines. This includes extracting common logic into reusable functions and adhering to consistent naming conventions and indentation. By doing so, you'll create clean, readable, and maintainable code that's easier to collaborate on and extend. #### Lab: - [**Write modular code by creating functions and organizing them into modules.**](https://spinncode.com/designs/ABBm5lDQ) #### Lab Summary: Writing modular code in Python by creating functions and organizing them into modules makes code more readable, maintainable, and reusable. Key benefits include improved readability, maintainability, and reusability. By applying best practices such as keeping modules focused on a single responsibility and using meaningful names, developers can create efficient and well-structured code. ### Week 4: Object-Oriented Programming (OOP) in Python #### Topics: - [**Introduction to Object-Oriented Programming: Classes, objects, and methods.**](https://spinncode.com/designs/zmrIg7SW): Learn the fundamentals of Object-Oriented Programming in Python, covering classes, objects, properties, and methods, and discover how to control access to these elements using access modifiers. You'll gain a deeper understanding of how to write efficient, readable, and maintainable code in Python. - [**Inheritance, polymorphism, encapsulation, and abstraction in Python.**](https://spinncode.com/designs/Jo1RONuW): Understand and apply Object-Oriented Programming concepts in Python, including inheritance, polymorphism, encapsulation, and abstraction, to write efficient, maintainable, and modular code. These fundamental concepts promote code reuse and improve code quality. Explore examples and learn how to implement these concepts in real-world applications. - [**Understanding magic methods (dunder methods) and operator overloading.**](https://spinncode.com/designs/MsR9eFF5): Learn how to define and use magic methods in Python, also known as dunder methods, to add custom behavior and override operator default behaviors. Explore practical examples and best practices for using magic methods to write efficient, readable, and maintainable Python code that integrates seamlessly with the Python ecosystem. - [**Design patterns in Python: Singleton, Factory, and others.**](https://spinncode.com/designs/jEJu2JR4): Discover design patterns in Python, including the Singleton, Factory, and Observer patterns, to improve your coding skills and write more maintainable, flexible, and scalable code. Learn how to implement these patterns with practical examples and take your Python programming to the next level. Understand the benefits of design patterns in software development and how to apply them to real-world projects. #### Lab: - [**Implement a class-based system with inheritance and polymorphism.**](https://spinncode.com/designs/b0t7vJIw) #### Lab Summary: Master Object-Oriented Programming in Python with inheritance and polymorphism. Learn how to define a base class and derived classes, and use method overriding to achieve polymorphism. Implement a class-based system with real-world examples and take your Python skills to the next level. ### Week 5: File Handling and Working with External Data #### Topics: - [**Reading and writing files (text, CSV, JSON) with Python.**](https://spinncode.com/designs/n0rSBvTg): Master the basics of reading and writing files in Python, including text, CSV, and JSON files, and learn best practices for file handling, such as using the `with` statement and handling errors effectively. This topic covers key concepts and provides practical exercises to help you develop essential file handling skills in Python. - [**Introduction to Python’s `pathlib` and `os` modules for file manipulation.**](https://spinncode.com/designs/X7mywenl): Learn how to effectively work with files and directories in Python using the built-in `os` and `pathlib` modules, including file creation, deletion, and manipulation, and best practices for choosing between the two. Understand the strengths and weaknesses of each module and learn how to use path objects and advanced path manipulation functions. - [**Working with external data sources: APIs, web scraping (using `requests` and `BeautifulSoup`).**](https://spinncode.com/designs/SPGH0LLj): Fetch and Extract External Data in Python with APIs and Web Scraping. Learn to work with external data using the requests library and BeautifulSoup, including fetching data from APIs and scraping websites like IMDB. - [**Error handling and exception management in file operations.**](https://spinncode.com/designs/LEqbcbyz): Mastering error handling in Python file operations is crucial for writing robust and reliable code. Learn best practices such as anticipating errors, being specific with exception types, and providing informative error messages to create more resilient file handling code. Explore practical examples of handling errors when reading and writing files in Python. #### Lab: - [**Build a script that processes data from files and external APIs.**](https://spinncode.com/designs/Dx27Ahdd) #### Lab Summary: Learn how to build a Python script that reads data from CSV, JSON, and text files, and fetches data from external APIs. Master file handling and API integration skills by following along with a comprehensive example that demonstrates how to merge data from multiple sources and write it to a new CSV file. ### Week 6: Testing and Debugging Python Code #### Topics: - [**Importance of testing in modern software development.**](https://spinncode.com/designs/4fgfI9l1): Testing plays a crucial role in modern software development, ensuring quality, reliability, and maintainability of software systems. Effective testing helps identify and fix defects, improve code quality, and increase confidence in the overall functionality of an application. By following best practices and leveraging popular tools such as Unittest, Pytest, and Mock, developers can write better code and deliver high-quality software. - [**Unit testing with Python’s `unittest` and `pytest` frameworks.**](https://spinncode.com/designs/fGUULRZC): Writing unit tests in Python using `unittest` and `pytest` frameworks is crucial for ensuring code quality and reliability. Learn key concepts, best practices, and how to get started with both frameworks to improve your development workflow. - [**Mocking and patching external dependencies in tests.**](https://spinncode.com/designs/Q1z59l8h): Techniques for isolating and testing code's interactions with external dependencies in Python, such as mocking and patching, are crucial for efficient testing. Python's "unittest.mock" library allows developers to create fake objects that mimic the behavior of external dependencies, making tests more reliable and less complex. Best practices for mocking and patching include using specific mock values and keeping mocks organized and maintainable. - [**Debugging techniques: Using `pdb` and logging for error tracking.**](https://spinncode.com/designs/zP60CDXq): Mastering two essential techniques in debugging Python code, this topic covers using the `pdb` module and logging for error tracking. By implementing these methods, developers can identify and fix errors more efficiently, reducing debugging time and improving code quality. Key takeaways include using `pdb` to step through code line by line and leveraging the `logging` module to track events and potential errors. #### Lab: - [**Write unit tests for a Python project using `pytest` and practice debugging techniques.**](https://spinncode.com/designs/rUdVF7ib) #### Lab Summary: Learn to write unit tests for Python projects using `pytest`, including how to set up and tear down test data with fixtures. Discover debugging techniques using `pdb` and logging to identify and fix code errors. Practice writing tests and debugging code with a hands-on exercise and explore additional resources for further learning. ### Week 7: Functional Programming in Python #### Topics: - [**Understanding the functional programming paradigm in Python.**](https://spinncode.com/designs/vxvPVlSm): Functional programming principles in Python, including pure functions, immutability, and higher-order functions, can lead to more composable and efficient code. Understanding concepts like data processing pipelines and concurrent programming help apply functional programming in practice. Mastering these concepts simplifies data processing and improves code predictability. - [**Using higher-order functions: `map()`, `filter()`, `reduce()`, and `lambda` functions.**](https://spinncode.com/designs/bHr7TOx3): Discover how to harness the power of Python's higher-order functions, including `map()`, `filter()`, `reduce()`, and `lambda` functions, to write more concise and declarative code. Learn through examples and practice exercises how these functions can help you abstract away low-level operations and improve your Python programming skills. - [**Working with immutability and recursion.**](https://spinncode.com/designs/4HYo1ue7): Immutability and recursion are key concepts in functional programming that can greatly improve code efficiency and predictability. Learn how to work with immutable objects and recursive functions in Python, and discover best practices for implementing these concepts in your code. - [**Introduction to Python’s `functools` and `itertools` libraries for advanced functional techniques.**](https://spinncode.com/designs/FrOGUBOG): Learn how to leverage Python's `functools` and `itertools` libraries for advanced functional programming. Discover how functions like `reduce()`, `partial()`, and `cycle()` can help you write more efficient and readable code. #### Lab: - [**Solve real-world problems using functional programming principles.**](https://spinncode.com/designs/NAcwR4CL) #### Lab Summary: Learn how to apply functional programming principles to solve real-world problems in Python, covering topics such as text processing, data analysis, and example use cases through two lab problems: text processing and data analysis. ### Week 8: Concurrency and Parallelism #### Topics: - [**Introduction to concurrent programming in Python.**](https://spinncode.com/designs/WYoHznuP): Improve your Python programming skills by learning about concurrency, its benefits, and how to implement it using multiprocessing, threading, and asyncio, to build efficient and scalable programs. Explore how asyncio allows for single-threaded concurrent code using coroutines and multiplexing I/O access. Discover how concurrency can enhance responsiveness, throughput, and resource utilization in Python programming. - [**Using threading and multiprocessing for parallel tasks.**](https://spinncode.com/designs/310fvTpb): Mastering concurrency in Python involves leveraging threading for I/O-bound tasks like downloads or user interaction, and utilizing multiprocessing for CPU-bound tasks such as data processing or scientific computing, with considerations for shared memory and cross-platform support. Weigh the differences between threading and multiprocessing to write efficient and scalable code. Effective use of concurrency enhances the performance of your Python programs. - [**Asynchronous programming with `asyncio` and coroutines.**](https://spinncode.com/designs/N0J6F8TY): Improve I/O-bound application performance with asynchronous programming in Python using the `asyncio` library. Discover key concepts like coroutines, event loops, futures, and tasks, and learn best practices for writing efficient and scalable code. Apply asynchronous programming to real-world scenarios like web scraping, I/O-bound operations, and real-time updates. - [**Comparing synchronous vs asynchronous workflows: When to use each.**](https://spinncode.com/designs/1iVX7WQw): Master the art of concurrent programming in Python with this in-depth comparison of synchronous and asynchronous workflows. Discover how to choose the right approach for your application, from CPU-bound tasks to I/O-bound operations, and learn best practices for integrating concurrency into your Python code. #### Lab: - [**Build a program that handles multiple tasks concurrently using `asyncio` and threading.**](https://spinncode.com/designs/h6nAVguW) #### Lab Summary: Learn how to leverage concurrency in Python to enhance application performance and responsiveness. This module explores using `asyncio` for single-threaded concurrent code and threading for multi-threaded concurrent code, as well as combining these techniques to handle multiple tasks simultaneously. Examples include fetching data from multiple websites and calculating sums in multiple lists using both `asyncio` and threading. ### Week 9: Data Science and Visualization with Python #### Topics: - [**Introduction to NumPy for numerical computing.**](https://spinncode.com/designs/yWbF1cAu): Learn how to work with NumPy, a library for efficient numerical computation in Python, including its key features, installation, and basic operations such as indexing, array operations, and matrix multiplication. Discover how to use vectorized operations, load numerical data from text files, and apply best practices for numerical computations. - [**Pandas for data manipulation and analysis.**](https://spinncode.com/designs/SX8EJq0h): Mastering data manipulation and analysis with Pandas. Learn how to efficiently handle and process data using key concepts, functions, and techniques such as data structures, missing data handling, merging, joining, and reshaping data for effective data science and visualization. - [**Visualizing data with Matplotlib and Seaborn.**](https://spinncode.com/designs/LJZUrXrQ): Learn to effectively visualize data using Matplotlib and Seaborn, two popular Python libraries for data science. Discover how to create simple plots and complex heatmaps, and understand best practices for creating informative visualizations. Master the basics of data visualization to gain insights and communicate findings from your data. - [**Exploratory data analysis (EDA) using real-world datasets.**](https://spinncode.com/designs/cMhKMBp7): This educational topic covers the process of exploratory data analysis (EDA) using real-world datasets and Python. Key steps in EDA discussed include loading and preprocessing data, calculating descriptive statistics, creating data visualizations, and performing correlation analysis. By completing these steps, data scientists can better understand their data and make informed decisions in their analysis or modeling. #### Lab: - [**Perform data analysis and visualization on a dataset using Pandas and Matplotlib.**](https://spinncode.com/designs/09KSETnn) #### Lab Summary: Discover how to analyze and visualize a real-world dataset using Pandas and Matplotlib. Learn to load and clean a dataset, explore and preprocess it, and create informative visualizations to gain valuable insights into the data. ### Week 10: Web Development with Python #### Topics: - [**Introduction to web development frameworks: Flask vs Django.**](https://spinncode.com/designs/no0fSY07): "Learn about the key differences between Flask and Django, two popular Python web development frameworks. Discover their strengths, use cases, and comparison, and see how to build a simple todo list app using both frameworks. This overview helps you decide which framework is best for your next project." - [**Building RESTful APIs with Flask/Django.**](https://spinncode.com/designs/kYbp4SpH): Building RESTful APIs in Python using Flask and Django. Learn the key design principles and follow step-by-step tutorials on how to create simple APIs with these popular frameworks, and discover what to do next to improve your skills. - [**Connecting to databases using SQLAlchemy (Flask) or Django ORM.**](https://spinncode.com/designs/FPIKDdrO): Learn how to connect to databases using SQLAlchemy with Flask and Django ORM, two popular Python tools. Understand the benefits and differences between SQLAlchemy and Django ORM, and implement best practices for querying data and managing database connections. - [**Best practices for securing web applications.**](https://spinncode.com/designs/VWknkgkX): Protect your web applications with these essential security best practices, including validating user input, defending against cross-site scripting (XSS) and cross-site request forgery (CSRF), safeguarding sensitive data, and using HTTPS. By implementing these measures, you can prevent data breaches and protect your users' trust. Learn how to secure your web applications built with Python. #### Lab: - [**Create a RESTful API with Flask/Django and interact with it using Python.**](https://spinncode.com/designs/VOrbyIT0) #### Lab Summary: Learn how to build RESTful APIs using Flask and Django, two popular Python web frameworks, including designing and implementing simple APIs, interacting with them using Python, and understanding key concepts like resources and stateless architecture. ### Week 11: Automation and Scripting #### Topics: - [**Introduction to scripting for automation (shell scripts, cron jobs).**](https://spinncode.com/designs/WqQIfRKH): Streamline tasks and reduce manual efforts by mastering shell scripts and cron jobs on Linux-based systems. Learn how to write and execute shell scripts for tasks such as file management and system configuration, and schedule them using cron jobs to run at specific times or intervals. - [**Automating repetitive tasks with Python.**](https://spinncode.com/designs/Fm4q2RF9): Python automation saves time by streamlining repetitive tasks. Learn how to automate tasks through scripting, leverage libraries such as `shutil` and `schedule`, and follow best practices to optimize your workflow. - [**Interacting with system processes using `subprocess` and `os` modules.**](https://spinncode.com/designs/dxjRn3vn): Interacting with system processes is crucial for automating tasks and integrating Python scripts with the operating system. The `subprocess` and `os` modules in Python provide a way to execute system commands, manage processes, and access environment variables. By using these modules together, developers can create robust and efficient automation scripts while minimizing security risks. - [**Working with Python for network automation and web scraping.**](https://spinncode.com/designs/e8lMKStx): Discover how to harness Python's power for network automation and web scraping, by learning to interact with network devices and extract data from websites using libraries such as `paramiko`, `BeautifulSoup`, and `Scrapy`. This knowledge can improve network efficiency, reduce downtime, and unlock valuable data insights. With practical examples and takeaways, you'll be able to automate tasks and scrape data like a pro. #### Lab: - [**Write scripts to automate tasks like file handling, data extraction, and network operations.**](https://spinncode.com/designs/QvMuaf7s) #### Lab Summary: Learn how to automate tasks like file handling, data extraction, and network operations using Python scripting. Discover how to write scripts that interact with the operating system, manipulate files, and perform network operations using libraries like `os`, `shutil`, `pandas`, and `paramiko`. Master practical examples, from creating file backups to web scraping and SSH automation. ### Week 12: Packaging, Version Control, and Deployment #### Topics: - [**Introduction to Python packaging: `setuptools` and `wheel`.**](https://spinncode.com/designs/Hvz6XfFj): Learn the essentials of Python packaging with `setuptools` and `wheel`, key tools for creating, distributing, and managing Python packages efficiently. Discover how to create well-structured packages, manage dependencies, and distribute them in a more efficient format. Master the fundamentals of package metadata management and project structure creation. - [**Creating and publishing Python packages (PyPI).**](https://spinncode.com/designs/UAkG0V3f): Creating and publishing Python packages on the Python Package Index (PyPI) is an essential skill for developers, allowing them to share and manage their code. This topic guides you through creating a Python package using setuptools and wheel, defining package metadata and dependencies, and uploading packages to PyPI using twine. By following these steps and best practices, developers can ensure their packages are secure, authentic, and easy to use. - [**Version control with Git: Managing and collaborating on Python projects.**](https://spinncode.com/designs/Bx4dUq1i): Manage and collaborate on Python projects efficiently with Git, learning essential concepts, commands, and best practices for version control, branching, and merging changes. Discover how to set up and use Git for Python projects, and explore collaboration methods for streamlined team workflow. - [**Deploying Python applications: Using Docker and cloud platforms.**](https://spinncode.com/designs/BiTKW2z6): Learn how to deploy Python applications using Docker and cloud platforms, covering the benefits of containerization, Docker fundamentals, and step-by-step deployment to AWS, Google Cloud, and Microsoft Azure. Discover how to create a Dockerfile, build a Docker image, and run containers on various cloud services. Explore the advantages of using Docker for fast, secure, and portable deployments. #### Lab: - [**Package a Python project and deploy it using Docker and Git.**](https://spinncode.com/designs/7CSmX7AS) #### Lab Summary: Learn how to package a Python project and deploy it using Docker and Git, with a focus on streamlining your development workflow through automated deployment and version control. This tutorial covers creating a source distribution, building a Docker image, and deploying to a production environment with GitHub Actions. ## Final Project - **Description:** Develop a full-fledged Python project that integrates concepts from multiple areas (e.g., web development, data science, automation). The project should demonstrate best practices in Python coding, testing, and deployment. - **Presentation:** Students will present their final projects with a live demo and discuss the design choices, challenges, and solutions. ## Grading Breakdown - **Assignments&Labs:** 40% - **MidtermProject:** 20% - **FinalProject:** 30% - **Participation&Quizzes:** 10%
Course Outline

Modern Python Programming: Best Practices and Trends

## Course Objectives - Gain a deep understanding of Python fundamentals and its modern ecosystem. - Learn best practices for writing clean, efficient, and scalable Python code. - Master popular Python libraries and frameworks for data science, web development, and automation. - Develop expertise in version control, testing, packaging, and deploying Python projects. ## Weekly Breakdown ### Week 1: Introduction to Python and Environment Setup #### Topics: - [**Overview of Python: History, popularity, and use cases.**](https://spinncode.com/designs/sBM9848p): Discover the history of Python, from its creation by Guido van Rossum to its current status as a top programming language. Learn about its popularity, real-world applications, and various use cases in web development, data science, machine learning, automation, gaming, and education. Explore how you can unlock opportunities with Python. - [**Setting up a Python development environment (Virtualenv, Pipenv, Conda).**](https://spinncode.com/designs/VYrvyzyQ): Discover how to set up a Python development environment using Virtualenv, Pipenv, or Conda, and learn why isolation, reproducibility, and efficient development are crucial for Python projects. Explore the key differences between these tools and choose the right one for your needs, enabling you to simplify troubleshooting and collaboration. - [**Introduction to Python's package manager (pip) and virtual environments.**](https://spinncode.com/designs/BLiZPR5D): Managing dependencies and isolating environments are crucial for efficient Python development. Learn about pip, Python's package manager, and how to work with virtual environments to streamline your workflow. Create self-contained environments for each project to ensure consistency and reduce errors. - [**Exploring Python's basic syntax: Variables, data types, control structures.**](https://spinncode.com/designs/UiOQqIel): Explore Python's basic syntax and control structures, including variables, data types, conditional statements, and loops, and discover how to apply them in real-world examples. Learn how to store and manipulate data, control the flow of your program, and make informed coding decisions. Mastering these fundamentals is crucial for building a strong foundation in Python programming. #### Lab: - [**Install Python, set up a virtual environment, and write your first Python script.**](https://spinncode.com/designs/XeKkzaFZ) #### Lab Summary: Learn how to install Python, set up a virtual environment, and write your first Python script, with step-by-step instructions and code examples to get you started with Python development. Discover the benefits of using virtual environments and how to manage dependencies for your project. Master the basics of running Python scripts and get ready to dive deeper into Python programming. ### Week 2: Data Structures and Basic Algorithms #### Topics: - [**Understanding Python’s built-in data types: Lists, tuples, dictionaries, sets.**](https://spinncode.com/designs/hXBlAwZr): Discover the fundamentals of Python's built-in data structures, including lists, tuples, dictionaries, and sets, and learn how to create and manipulate them with key methods and operations. Understand the differences between these data types, including mutability, ordering, and memory efficiency, and solidify your understanding with practical exercises. - [**Working with iterators and generators for efficient looping.**](https://spinncode.com/designs/JSK1hD2a): Discover how to work efficiently with large datasets in Python using iterators and generators, and learn how these tools improve performance, scalability, and memory efficiency in your programs. You'll gain hands-on experience with creating custom iterators and generators using real-world examples and understand how to apply them to streamline your code. Take your Python skills to the next level by mastering these essential concepts. - [**Comprehensions (list, dict, set comprehensions) for concise code.**](https://spinncode.com/designs/BZiSWGyh): Learn the fundamentals of Python comprehensions and how to use them to write concise, readable, and efficient code. Discover the different types of comprehensions in Python, including list, dict, and set comprehensions, and how to use conditional statements to filter elements. Mastering comprehensions will take your Python coding skills to the next level. - [**Basic algorithms: Sorting, searching, and common patterns.**](https://spinncode.com/designs/PmKbOEYP): Discover the fundamental algorithms in Python programming, including sorting algorithms like Bubble Sort, Selection Sort, and Insertion Sort, as well as searching algorithms like Linear Search and Binary Search. Learn how to implement these algorithms efficiently and effectively in Python, and explore the built-in sorting and searching algorithms available in the language. #### Lab: - [**Implement data manipulation tasks using lists, dictionaries, and comprehensions.**](https://spinncode.com/designs/r1fgEtbZ) #### Lab Summary: Master the fundamentals of data manipulation in Python using lists, dictionaries, and comprehensions to efficiently store, access, and transform data. Learn essential techniques for working with ordered data in lists, key-value pairs in dictionaries, and concise data creation with comprehensions. ### Week 3: Functions, Modules, and Best Practices #### Topics: - [**Defining and using functions: Arguments, return values, and scope.**](https://spinncode.com/designs/GUUudtly): Discover the power of functions in Python, including how to define and use them, function arguments, return values, scope, and local variables, plus best practices for writing efficient and readable code. Learn to write functions that reduce code duplication, improve reusability, and enhance code readability. Explore expert tips and resources to master Python functions. - [**Understanding Python’s module system and creating reusable code.**](https://spinncode.com/designs/7qEqpPof): Learn the fundamentals of Python's module system, how to create reusable code, and best practices for organizing and importing modules in Python, to write more maintainable and scalable code. Discover how to create modules, import them into other projects, and customize the module search path. - [**Using built-in modules and the Python Standard Library.**](https://spinncode.com/designs/WcsocEsL): Mastering Python's built-in modules and Standard Library can significantly streamline your coding process. Explore commonly used modules like math, random, time, and os, and learn how to use them in your Python code, enabling you to write more efficient and effective programs. - [**Best practices: DRY (Don’t Repeat Yourself), writing clean and readable code (PEP 8).**](https://spinncode.com/designs/c92j1nQY): Write more efficient Python code by applying the Don't Repeat Yourself principle and following PEP 8 guidelines. This includes extracting common logic into reusable functions and adhering to consistent naming conventions and indentation. By doing so, you'll create clean, readable, and maintainable code that's easier to collaborate on and extend. #### Lab: - [**Write modular code by creating functions and organizing them into modules.**](https://spinncode.com/designs/ABBm5lDQ) #### Lab Summary: Writing modular code in Python by creating functions and organizing them into modules makes code more readable, maintainable, and reusable. Key benefits include improved readability, maintainability, and reusability. By applying best practices such as keeping modules focused on a single responsibility and using meaningful names, developers can create efficient and well-structured code. ### Week 4: Object-Oriented Programming (OOP) in Python #### Topics: - [**Introduction to Object-Oriented Programming: Classes, objects, and methods.**](https://spinncode.com/designs/zmrIg7SW): Learn the fundamentals of Object-Oriented Programming in Python, covering classes, objects, properties, and methods, and discover how to control access to these elements using access modifiers. You'll gain a deeper understanding of how to write efficient, readable, and maintainable code in Python. - [**Inheritance, polymorphism, encapsulation, and abstraction in Python.**](https://spinncode.com/designs/Jo1RONuW): Understand and apply Object-Oriented Programming concepts in Python, including inheritance, polymorphism, encapsulation, and abstraction, to write efficient, maintainable, and modular code. These fundamental concepts promote code reuse and improve code quality. Explore examples and learn how to implement these concepts in real-world applications. - [**Understanding magic methods (dunder methods) and operator overloading.**](https://spinncode.com/designs/MsR9eFF5): Learn how to define and use magic methods in Python, also known as dunder methods, to add custom behavior and override operator default behaviors. Explore practical examples and best practices for using magic methods to write efficient, readable, and maintainable Python code that integrates seamlessly with the Python ecosystem. - [**Design patterns in Python: Singleton, Factory, and others.**](https://spinncode.com/designs/jEJu2JR4): Discover design patterns in Python, including the Singleton, Factory, and Observer patterns, to improve your coding skills and write more maintainable, flexible, and scalable code. Learn how to implement these patterns with practical examples and take your Python programming to the next level. Understand the benefits of design patterns in software development and how to apply them to real-world projects. #### Lab: - [**Implement a class-based system with inheritance and polymorphism.**](https://spinncode.com/designs/b0t7vJIw) #### Lab Summary: Master Object-Oriented Programming in Python with inheritance and polymorphism. Learn how to define a base class and derived classes, and use method overriding to achieve polymorphism. Implement a class-based system with real-world examples and take your Python skills to the next level. ### Week 5: File Handling and Working with External Data #### Topics: - [**Reading and writing files (text, CSV, JSON) with Python.**](https://spinncode.com/designs/n0rSBvTg): Master the basics of reading and writing files in Python, including text, CSV, and JSON files, and learn best practices for file handling, such as using the `with` statement and handling errors effectively. This topic covers key concepts and provides practical exercises to help you develop essential file handling skills in Python. - [**Introduction to Python’s `pathlib` and `os` modules for file manipulation.**](https://spinncode.com/designs/X7mywenl): Learn how to effectively work with files and directories in Python using the built-in `os` and `pathlib` modules, including file creation, deletion, and manipulation, and best practices for choosing between the two. Understand the strengths and weaknesses of each module and learn how to use path objects and advanced path manipulation functions. - [**Working with external data sources: APIs, web scraping (using `requests` and `BeautifulSoup`).**](https://spinncode.com/designs/SPGH0LLj): Fetch and Extract External Data in Python with APIs and Web Scraping. Learn to work with external data using the requests library and BeautifulSoup, including fetching data from APIs and scraping websites like IMDB. - [**Error handling and exception management in file operations.**](https://spinncode.com/designs/LEqbcbyz): Mastering error handling in Python file operations is crucial for writing robust and reliable code. Learn best practices such as anticipating errors, being specific with exception types, and providing informative error messages to create more resilient file handling code. Explore practical examples of handling errors when reading and writing files in Python. #### Lab: - [**Build a script that processes data from files and external APIs.**](https://spinncode.com/designs/Dx27Ahdd) #### Lab Summary: Learn how to build a Python script that reads data from CSV, JSON, and text files, and fetches data from external APIs. Master file handling and API integration skills by following along with a comprehensive example that demonstrates how to merge data from multiple sources and write it to a new CSV file. ### Week 6: Testing and Debugging Python Code #### Topics: - [**Importance of testing in modern software development.**](https://spinncode.com/designs/4fgfI9l1): Testing plays a crucial role in modern software development, ensuring quality, reliability, and maintainability of software systems. Effective testing helps identify and fix defects, improve code quality, and increase confidence in the overall functionality of an application. By following best practices and leveraging popular tools such as Unittest, Pytest, and Mock, developers can write better code and deliver high-quality software. - [**Unit testing with Python’s `unittest` and `pytest` frameworks.**](https://spinncode.com/designs/fGUULRZC): Writing unit tests in Python using `unittest` and `pytest` frameworks is crucial for ensuring code quality and reliability. Learn key concepts, best practices, and how to get started with both frameworks to improve your development workflow. - [**Mocking and patching external dependencies in tests.**](https://spinncode.com/designs/Q1z59l8h): Techniques for isolating and testing code's interactions with external dependencies in Python, such as mocking and patching, are crucial for efficient testing. Python's "unittest.mock" library allows developers to create fake objects that mimic the behavior of external dependencies, making tests more reliable and less complex. Best practices for mocking and patching include using specific mock values and keeping mocks organized and maintainable. - [**Debugging techniques: Using `pdb` and logging for error tracking.**](https://spinncode.com/designs/zP60CDXq): Mastering two essential techniques in debugging Python code, this topic covers using the `pdb` module and logging for error tracking. By implementing these methods, developers can identify and fix errors more efficiently, reducing debugging time and improving code quality. Key takeaways include using `pdb` to step through code line by line and leveraging the `logging` module to track events and potential errors. #### Lab: - [**Write unit tests for a Python project using `pytest` and practice debugging techniques.**](https://spinncode.com/designs/rUdVF7ib) #### Lab Summary: Learn to write unit tests for Python projects using `pytest`, including how to set up and tear down test data with fixtures. Discover debugging techniques using `pdb` and logging to identify and fix code errors. Practice writing tests and debugging code with a hands-on exercise and explore additional resources for further learning. ### Week 7: Functional Programming in Python #### Topics: - [**Understanding the functional programming paradigm in Python.**](https://spinncode.com/designs/vxvPVlSm): Functional programming principles in Python, including pure functions, immutability, and higher-order functions, can lead to more composable and efficient code. Understanding concepts like data processing pipelines and concurrent programming help apply functional programming in practice. Mastering these concepts simplifies data processing and improves code predictability. - [**Using higher-order functions: `map()`, `filter()`, `reduce()`, and `lambda` functions.**](https://spinncode.com/designs/bHr7TOx3): Discover how to harness the power of Python's higher-order functions, including `map()`, `filter()`, `reduce()`, and `lambda` functions, to write more concise and declarative code. Learn through examples and practice exercises how these functions can help you abstract away low-level operations and improve your Python programming skills. - [**Working with immutability and recursion.**](https://spinncode.com/designs/4HYo1ue7): Immutability and recursion are key concepts in functional programming that can greatly improve code efficiency and predictability. Learn how to work with immutable objects and recursive functions in Python, and discover best practices for implementing these concepts in your code. - [**Introduction to Python’s `functools` and `itertools` libraries for advanced functional techniques.**](https://spinncode.com/designs/FrOGUBOG): Learn how to leverage Python's `functools` and `itertools` libraries for advanced functional programming. Discover how functions like `reduce()`, `partial()`, and `cycle()` can help you write more efficient and readable code. #### Lab: - [**Solve real-world problems using functional programming principles.**](https://spinncode.com/designs/NAcwR4CL) #### Lab Summary: Learn how to apply functional programming principles to solve real-world problems in Python, covering topics such as text processing, data analysis, and example use cases through two lab problems: text processing and data analysis. ### Week 8: Concurrency and Parallelism #### Topics: - [**Introduction to concurrent programming in Python.**](https://spinncode.com/designs/WYoHznuP): Improve your Python programming skills by learning about concurrency, its benefits, and how to implement it using multiprocessing, threading, and asyncio, to build efficient and scalable programs. Explore how asyncio allows for single-threaded concurrent code using coroutines and multiplexing I/O access. Discover how concurrency can enhance responsiveness, throughput, and resource utilization in Python programming. - [**Using threading and multiprocessing for parallel tasks.**](https://spinncode.com/designs/310fvTpb): Mastering concurrency in Python involves leveraging threading for I/O-bound tasks like downloads or user interaction, and utilizing multiprocessing for CPU-bound tasks such as data processing or scientific computing, with considerations for shared memory and cross-platform support. Weigh the differences between threading and multiprocessing to write efficient and scalable code. Effective use of concurrency enhances the performance of your Python programs. - [**Asynchronous programming with `asyncio` and coroutines.**](https://spinncode.com/designs/N0J6F8TY): Improve I/O-bound application performance with asynchronous programming in Python using the `asyncio` library. Discover key concepts like coroutines, event loops, futures, and tasks, and learn best practices for writing efficient and scalable code. Apply asynchronous programming to real-world scenarios like web scraping, I/O-bound operations, and real-time updates. - [**Comparing synchronous vs asynchronous workflows: When to use each.**](https://spinncode.com/designs/1iVX7WQw): Master the art of concurrent programming in Python with this in-depth comparison of synchronous and asynchronous workflows. Discover how to choose the right approach for your application, from CPU-bound tasks to I/O-bound operations, and learn best practices for integrating concurrency into your Python code. #### Lab: - [**Build a program that handles multiple tasks concurrently using `asyncio` and threading.**](https://spinncode.com/designs/h6nAVguW) #### Lab Summary: Learn how to leverage concurrency in Python to enhance application performance and responsiveness. This module explores using `asyncio` for single-threaded concurrent code and threading for multi-threaded concurrent code, as well as combining these techniques to handle multiple tasks simultaneously. Examples include fetching data from multiple websites and calculating sums in multiple lists using both `asyncio` and threading. ### Week 9: Data Science and Visualization with Python #### Topics: - [**Introduction to NumPy for numerical computing.**](https://spinncode.com/designs/yWbF1cAu): Learn how to work with NumPy, a library for efficient numerical computation in Python, including its key features, installation, and basic operations such as indexing, array operations, and matrix multiplication. Discover how to use vectorized operations, load numerical data from text files, and apply best practices for numerical computations. - [**Pandas for data manipulation and analysis.**](https://spinncode.com/designs/SX8EJq0h): Mastering data manipulation and analysis with Pandas. Learn how to efficiently handle and process data using key concepts, functions, and techniques such as data structures, missing data handling, merging, joining, and reshaping data for effective data science and visualization. - [**Visualizing data with Matplotlib and Seaborn.**](https://spinncode.com/designs/LJZUrXrQ): Learn to effectively visualize data using Matplotlib and Seaborn, two popular Python libraries for data science. Discover how to create simple plots and complex heatmaps, and understand best practices for creating informative visualizations. Master the basics of data visualization to gain insights and communicate findings from your data. - [**Exploratory data analysis (EDA) using real-world datasets.**](https://spinncode.com/designs/cMhKMBp7): This educational topic covers the process of exploratory data analysis (EDA) using real-world datasets and Python. Key steps in EDA discussed include loading and preprocessing data, calculating descriptive statistics, creating data visualizations, and performing correlation analysis. By completing these steps, data scientists can better understand their data and make informed decisions in their analysis or modeling. #### Lab: - [**Perform data analysis and visualization on a dataset using Pandas and Matplotlib.**](https://spinncode.com/designs/09KSETnn) #### Lab Summary: Discover how to analyze and visualize a real-world dataset using Pandas and Matplotlib. Learn to load and clean a dataset, explore and preprocess it, and create informative visualizations to gain valuable insights into the data. ### Week 10: Web Development with Python #### Topics: - [**Introduction to web development frameworks: Flask vs Django.**](https://spinncode.com/designs/no0fSY07): "Learn about the key differences between Flask and Django, two popular Python web development frameworks. Discover their strengths, use cases, and comparison, and see how to build a simple todo list app using both frameworks. This overview helps you decide which framework is best for your next project." - [**Building RESTful APIs with Flask/Django.**](https://spinncode.com/designs/kYbp4SpH): Building RESTful APIs in Python using Flask and Django. Learn the key design principles and follow step-by-step tutorials on how to create simple APIs with these popular frameworks, and discover what to do next to improve your skills. - [**Connecting to databases using SQLAlchemy (Flask) or Django ORM.**](https://spinncode.com/designs/FPIKDdrO): Learn how to connect to databases using SQLAlchemy with Flask and Django ORM, two popular Python tools. Understand the benefits and differences between SQLAlchemy and Django ORM, and implement best practices for querying data and managing database connections. - [**Best practices for securing web applications.**](https://spinncode.com/designs/VWknkgkX): Protect your web applications with these essential security best practices, including validating user input, defending against cross-site scripting (XSS) and cross-site request forgery (CSRF), safeguarding sensitive data, and using HTTPS. By implementing these measures, you can prevent data breaches and protect your users' trust. Learn how to secure your web applications built with Python. #### Lab: - [**Create a RESTful API with Flask/Django and interact with it using Python.**](https://spinncode.com/designs/VOrbyIT0) #### Lab Summary: Learn how to build RESTful APIs using Flask and Django, two popular Python web frameworks, including designing and implementing simple APIs, interacting with them using Python, and understanding key concepts like resources and stateless architecture. ### Week 11: Automation and Scripting #### Topics: - [**Introduction to scripting for automation (shell scripts, cron jobs).**](https://spinncode.com/designs/WqQIfRKH): Streamline tasks and reduce manual efforts by mastering shell scripts and cron jobs on Linux-based systems. Learn how to write and execute shell scripts for tasks such as file management and system configuration, and schedule them using cron jobs to run at specific times or intervals. - [**Automating repetitive tasks with Python.**](https://spinncode.com/designs/Fm4q2RF9): Python automation saves time by streamlining repetitive tasks. Learn how to automate tasks through scripting, leverage libraries such as `shutil` and `schedule`, and follow best practices to optimize your workflow. - [**Interacting with system processes using `subprocess` and `os` modules.**](https://spinncode.com/designs/dxjRn3vn): Interacting with system processes is crucial for automating tasks and integrating Python scripts with the operating system. The `subprocess` and `os` modules in Python provide a way to execute system commands, manage processes, and access environment variables. By using these modules together, developers can create robust and efficient automation scripts while minimizing security risks. - [**Working with Python for network automation and web scraping.**](https://spinncode.com/designs/e8lMKStx): Discover how to harness Python's power for network automation and web scraping, by learning to interact with network devices and extract data from websites using libraries such as `paramiko`, `BeautifulSoup`, and `Scrapy`. This knowledge can improve network efficiency, reduce downtime, and unlock valuable data insights. With practical examples and takeaways, you'll be able to automate tasks and scrape data like a pro. #### Lab: - [**Write scripts to automate tasks like file handling, data extraction, and network operations.**](https://spinncode.com/designs/QvMuaf7s) #### Lab Summary: Learn how to automate tasks like file handling, data extraction, and network operations using Python scripting. Discover how to write scripts that interact with the operating system, manipulate files, and perform network operations using libraries like `os`, `shutil`, `pandas`, and `paramiko`. Master practical examples, from creating file backups to web scraping and SSH automation. ### Week 12: Packaging, Version Control, and Deployment #### Topics: - [**Introduction to Python packaging: `setuptools` and `wheel`.**](https://spinncode.com/designs/Hvz6XfFj): Learn the essentials of Python packaging with `setuptools` and `wheel`, key tools for creating, distributing, and managing Python packages efficiently. Discover how to create well-structured packages, manage dependencies, and distribute them in a more efficient format. Master the fundamentals of package metadata management and project structure creation. - [**Creating and publishing Python packages (PyPI).**](https://spinncode.com/designs/UAkG0V3f): Creating and publishing Python packages on the Python Package Index (PyPI) is an essential skill for developers, allowing them to share and manage their code. This topic guides you through creating a Python package using setuptools and wheel, defining package metadata and dependencies, and uploading packages to PyPI using twine. By following these steps and best practices, developers can ensure their packages are secure, authentic, and easy to use. - [**Version control with Git: Managing and collaborating on Python projects.**](https://spinncode.com/designs/Bx4dUq1i): Manage and collaborate on Python projects efficiently with Git, learning essential concepts, commands, and best practices for version control, branching, and merging changes. Discover how to set up and use Git for Python projects, and explore collaboration methods for streamlined team workflow. - [**Deploying Python applications: Using Docker and cloud platforms.**](https://spinncode.com/designs/BiTKW2z6): Learn how to deploy Python applications using Docker and cloud platforms, covering the benefits of containerization, Docker fundamentals, and step-by-step deployment to AWS, Google Cloud, and Microsoft Azure. Discover how to create a Dockerfile, build a Docker image, and run containers on various cloud services. Explore the advantages of using Docker for fast, secure, and portable deployments. #### Lab: - [**Package a Python project and deploy it using Docker and Git.**](https://spinncode.com/designs/7CSmX7AS) #### Lab Summary: Learn how to package a Python project and deploy it using Docker and Git, with a focus on streamlining your development workflow through automated deployment and version control. This tutorial covers creating a source distribution, building a Docker image, and deploying to a production environment with GitHub Actions. ## Final Project - **Description:** Develop a full-fledged Python project that integrates concepts from multiple areas (e.g., web development, data science, automation). The project should demonstrate best practices in Python coding, testing, and deployment. - **Presentation:** Students will present their final projects with a live demo and discuss the design choices, challenges, and solutions. ## Grading Breakdown - **Assignments&Labs:** 40% - **MidtermProject:** 20% - **FinalProject:** 30% - **Participation&Quizzes:** 10%

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