Advanced Python

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About the Course

This course takes a deep dive into advanced Python concepts, focusing on building robust, scalable, and high-performance applications. Participants will explore topics such as object-oriented programming, concurrency, performance optimization, and more, while working with real-world use cases. Suitable for learners looking to refine their Python skills for professional development.

Curriculum

  • Module 1: Object-Oriented Programming (OOP) in Python
    DESCRIPTION

    Overview:

    This module covers advanced object-oriented programming techniques in Python, including inheritance, polymorphism, abstraction, interfaces, and mixins.

    Topics to Cover:

    • Inheritance and polymorphism
    • Abstraction and encapsulation
    • Creating interfaces and mixins
    • Real-world examples of OOP in Python

  • Module 2: Advanced Iterators, Generators, and Context Managers
    DESCRIPTION

    Overview:

    This module explores Python’s advanced iterator and generator concepts, and the use of context managers for efficient resource management.

    Topics to Cover:

    • Custom iterators
    • Generators and yield
    • Using and creating context managers (with statement)

  • Module 3: Decorators and Metaclasses
    DESCRIPTION

    Overview:

    In this module, participants will learn about decorators and metaclasses, how they work, and how they are used to modify or control class and function behavior dynamically.

    Topics to Cover:

    • Function and class decorators
    • Custom decorators
    • Introduction to metaclasses
    • Creating and using custom metaclasses

  • Module 4: Concurrency & Parallelism
    DESCRIPTION

    Overview:

    This module delves into Python’s concurrency and parallelism capabilities, focusing on asyncio, threading, multiprocessing, and concurrent execution.

    Topics to Cover:

    • Introduction to threading and multiprocessing
    • Working with asyncio (optional)
    • Understanding parallelism vs concurrency
    • Implementing concurrent tasks in Python applications

  • Module 5: Performance Optimization
    DESCRIPTION

    Overview:

    Participants will learn how to optimize the performance of Python applications by understanding memory management, the Global Interpreter Lock (GIL), and caching techniques.

    Topics to Cover:

    • Python memory management and garbage collection
    • Overcoming the Global Interpreter Lock (GIL)
    • Performance profiling and benchmarking
    • Caching with functools and other optimization techniques

  • Module 6: Testing and Debugging
    DESCRIPTION

    Overview:

    This module focuses on testing and debugging Python code, emphasizing the use of pytest, unit testing, and the pdb debugger for more reliable and maintainable code.

    Topics to Cover:

    • Unit testing with pytest and unittest
    • Test-driven development (TDD)
    • Debugging with pdb
    • Use cases in data engineering, machine learning, and AI

  • Module 7: Building REST APIs (Flask & FastAPI)
    DESCRIPTION

    Overview:

    This module introduces REST API development using Flask and FastAPI, with a focus on CRUD operations, asynchronous APIs, and RESTful principles.

    Topics to Cover:

    • RESTful API principles
    • Building APIs with Flask
    • Creating async APIs with FastAPI
    • Practical CRUD API development

  • Module 8: Working with Databases (SQLAlchemy)
    DESCRIPTION

    Overview:

    Participants will learn how to use SQLAlchemy for object-relational mapping (ORM) in Python, focusing on database queries, migrations, and optimization techniques.

    Topics to Cover:

    • Introduction to SQLAlchemy ORM
    • Database migrations
    • Query optimization techniques
    • Establishing database connections and interactions

  • Module 9: Working with APIs and Web Scraping
    DESCRIPTION

    Overview:

    This module covers the fundamentals of API integration and web scraping, focusing on requests and scrapy for extracting data from web resources.

    Topics to Cover:

    • API calls using requests
    • Web scraping basics with scrapy
    • Handling rate limits and proxies
    • Practical web scraping use cases

  • Module 10: How to Build a Python Package
    DESCRIPTION

    Overview:

    This module introduces the process of creating Python packages, structuring them for distribution, and versioning using setup.py.

    Topics to Cover:

    • Structuring a Python package
    • Creating and managing setup.py
    • Version control and documentation
    • Testing Python packages for distribution

  • Module 11: How to Execute Python from Command Line (ArgParse)
    DESCRIPTION

    Overview:

    Participants will learn to create command-line utilities using Python’s argparse module, focusing on argument parsing and execution from the command line.

    Topics to Cover:

    • Introduction to argparse
    • Parsing command-line arguments
    • Creating simple command-line utilities

  • Module 12: Regular Expressions (Regex)
    DESCRIPTION

    Overview:

    This module introduces advanced regular expression techniques for pattern matching, with practical use cases like extracting data from URLs and other text patterns.

    Topics to Cover:

    • Basic and advanced regex operations
    • Pattern matching for complex data extraction
    • Real-world use cases such as extracting LinkedIn profile names from URLs

Learning Outcomes

By the end of this course, participants will be able to:

  • Implement advanced object-oriented programming techniques in Python.
  • Utilize iterators, generators, and context managers effectively.
  • Create and apply decorators and metaclasses.
  • Build concurrent and parallel applications with Python.
  • Optimize Python code for performance and memory efficiency.
  • Develop and test Python REST APIs using Flask and FastAPI.
  • Manage and interact with databases using SQLAlchemy.
  • Build and distribute Python packages.
  • Perform web scraping and interact with APIs.
  • Create command-line tools using argparse.
  • Use advanced regular expressions for pattern matching.

Tools

IDEs and Editors: Visual Studio Code, Jupyter Notebooks
Virtual Environment & Libraries: venv, Python Libraries
Frameworks: Flask, FastAPI
ORM: SQLAlchemy
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FAQ

Frequently asked questions about the bootcamp

The course is structured into weekly modules, each containing video lectures, reading materials, assignments, and quizzes. You can complete the modules at your own pace, but we recommend following the weekly schedule to stay on track.

You can get support in multiple ways:

  • TA Support on Slack: Our teaching assistants are available on Slack to answer your questions and provide guidance.
  • Peer Community on Discord: Join our Discord community to discuss course topics, share ideas, and collaborate with fellow students.

TAs are available on Slack from 9 AM to 6 PM (ET) Monday to Friday. Outside these hours, you can still post your questions, and TAs will respond as soon as they are back online.

After enrolling in the course, you will receive an invitation link to join the Discord community. Follow the link to create an account or log in to your existing account.

The Discord community offers peer-to-peer support, where you can discuss course topics, share resources, collaborate on projects, and network with fellow learners

The optional mentoring service includes one-on-one sessions with an experienced mentor who can provide personalized guidance, feedback on your progress, and help you set and achieve your learning goals.

Please talk to our Program Advisors to sign up for Mentorship services for an additional cost

Yes, you will have lifetime access to the course materials, including any updates made to the content in the future.

We accept all major credit cards, PayPal, and bank transfers. You can choose your preferred payment method at checkout

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