Advanced Python Lesson Plan (15 Weeks, 3 Lectures per Week)

Objective

To master advanced Python concepts for efficient problem-solving, software development, and data manipulation.

Prerequisites

Strong understanding of Python basics (syntax, loops, functions, OOP)
Familiarity with libraries like NumPy, Pandas, and Matplotlib

Module 1: Pythonic Programming (Week 1)

Lecture 1: List comprehensions, generator expressions, and lambda functions Lecture 2: Map, filter, reduce, and common use cases Lecture 3: Project: Refactor a script using Pythonic techniques

Module 2: Functional Programming (Week 2)

Lecture 1: Higher-order functions and closures Lecture 2: Decorators, partial functions, and currying Lecture 3: Project: Build a utility package with decorators

Module 3: Advanced OOP Concepts (Weeks 3-4)

Week 3, Lecture 1: Metaclasses and dynamic classes Week 3, Lecture 2: Dunder methods and operator overloading Week 3, Lecture 3: Encapsulation, inheritance, and polymorphism Week 4, Lecture 1: Class decorators and property methods Week 4, Lecture 2: Design patterns in Python Week 4, Lecture 3: Project: Role-based access control system

Lesson 1: Introduction to OOP

Objective: Understand the basics of OOP and its importance.
Topics Covered:
- What is OOP?
- Benefits of OOP: Reusability, Encapsulation, Abstraction, Inheritance, and Polymorphism.
- OOP vs. Procedural Programming
Activities: Discuss real-life examples of OOP (e.g., car, bank account).
Exercise: Identify objects and attributes in a classroom scenario.

Lesson 2: Classes and Objects

Objective: Define and create classes and objects in Python.
Topics Covered:
- Defining a class using class keyword
- Creating objects and accessing attributes
- __init__ method and instance variables
Activities:
- Create a Car class with attributes (make, model, year).
- Create multiple car objects and print details.
Exercise: Create a Student class with name, age, and grade.

Lesson 3: Methods and Encapsulation

Objective: Understand methods, encapsulation, and access control.
Topics Covered:
- Instance methods and self
- Public, private, and protected members
- Getter and Setter methods
Activities:
- Implement a BankAccount class with deposit, withdraw, and balance methods.
Exercise: Implement a Book class with title, author, and price. Use encapsulation to control price updates.

Lesson 4: Inheritance and Polymorphism

Objective: Learn inheritance and method overriding.
Topics Covered:
- Creating subclasses
- Overriding methods
- Using super()
- Polymorphism (Duck Typing and Method Overloading)
Activities:
- Create a Vehicle class and derive Car and Bike classes.
- Implement polymorphism using a common method.
Exercise: Create a Shape base class and derive Circle, Square, and Rectangle with overridden area methods.

Lesson 5: Abstraction and Interfaces

Objective: Implement abstraction using abstract classes and interfaces.
Topics Covered:
- Using abc module for abstract classes
- Creating interfaces and enforcing method implementation
Activities:
- Create an abstract class Animal with abstract method sound().
Exercise: Implement Dog and Cat classes from the Animal abstract class.

Lesson 6: OOP Best Practices and Advanced Concepts

Objective: Learn best practices and advanced OOP concepts.
Topics Covered:
- SOLID principles
- Magic/Dunder methods (__str__, __repr__, __eq__, etc.)
- Composition vs. Inheritance
Activities:
- Implement a library management system using composition.
Exercise: Enhance the Student class to handle GPA calculations using magic methods.

Lesson 7: Project: Inventory Management System

Objective: Apply all OOP concepts in a practical project.
Activities:
- Design and build an inventory management system with CRUD operations.
- Implement inheritance, encapsulation, and polymorphism.
- Create reports using class methods.

Module 4: Error Handling and Context Managers (Week 5)

Lecture 1: Exception hierarchy, custom exceptions Lecture 2: Context managers and the ‘with’ statement Lecture 3: Project: Robust file processing application

Module 5: Iterators, Generators, and Coroutines (Weeks 6-7)

Week 6, Lecture 1: Iterators and iterables Week 6, Lecture 2: Generator functions and expressions Week 6, Lecture 3: Project: Custom data stream generator Week 7, Lecture 1: Asynchronous programming with asyncio Week 7, Lecture 2: Coroutines and event loops Week 7, Lecture 3: Project: Real-time data streaming app

Module 6: Multithreading, Multiprocessing, and Concurrency (Weeks 8-9)

Week 8, Lecture 1: Threading and multiprocessing overview Week 8, Lecture 2: Synchronization, locks, and queues Week 8, Lecture 3: Project: Parallel web scraper Week 9, Lecture 1: Asyncio and concurrency patterns Week 9, Lecture 2: Handling concurrency issues Week 9, Lecture 3: Project: Async web scraper

Module 7: Metaprogramming and Introspection (Week 10)

Lecture 1: Dynamic code execution (eval, exec) Lecture 2: Introspection and reflection Lecture 3: Project: Plugin-based architecture

Module 8: Advanced Libraries and Frameworks (Weeks 11-12)

Week 11, Lecture 1: SQLAlchemy and ORMs Week 11, Lecture 2: Celery for task scheduling Week 11, Lecture 3: Pydantic for data validation Week 12, Lecture 1: Advanced use cases Week 12, Lecture 2: Framework integration Week 12, Lecture 3: Project: Task scheduler with Celery

Module 9: Performance Optimization (Week 13)

Lecture 1: Profiling and benchmarking Lecture 2: Memory management and garbage collection Lecture 3: Project: Optimize a complex algorithm

Module 10: Security and Best Practices (Week 14)

Lecture 1: Secure coding practices Lecture 2: Encryption and hashing Lecture 3: Project: Secure data transmission app

Capstone Project (Week 15)

Lecture 1: Project planning and scoping Lecture 2: Development and review Lecture 3: Final presentation and assessment

Evaluation and Feedback

Weekly quizzes
Project reviews
Final assessment

Expected Outcome

Learners will be proficient in advanced Python techniques, ready for software development or data science roles.