Prerequisites:

• Basic understanding of Python syntax, data types, control flow, and functions.
• Familiarity with fundamental programming concepts like loops, conditionals, and modules.

Course Duration: 4 weeks (adjust based on specific content)

Course Structure:

Each week will focus on a specific theme, with lectures, coding exercises, and hands-on projects to reinforce your learning.

Week 1: Advanced Data Structures and Algorithms

• Lists, Tuples, and Dictionaries: Deep dive into advanced operations, list comprehensions, nested data structures, and dictionary methods.
• Sets and Queues: Explore unique functionalities of sets and queues, and implement them in practical scenarios.
• Stacks and Deques: Understand stack operations like push, pop, and peek, and utilize deques for efficient data manipulation.
• Algorithm Design and Analysis: Introduce fundamental algorithms like sorting, searching, and recursion, and analyze their time and space complexity.

Week 2: Object-Oriented Programming (OOP)

• Classes and Objects: Define custom classes, create object instances, and understand the relationship between them.
• Inheritance and Polymorphism: Leverage inheritance for code reuse and polymorphism for flexible object interaction.
• Encapsulation and Abstraction: Implement data hiding and abstraction principles for secure and maintainable code.
• Special Methods (Dunder methods): Explore magic methods like init, str, and add to customize object behavior.

Week 3: Powerful Python Libraries

• NumPy: Master data manipulation and vectorized operations for efficient scientific computing and numerical analysis.
• Pandas: Explore powerful data structures like DataFrames and Series for data analysis, manipulation, and visualization.
• Matplotlib and Seaborn: Create stunning data visualizations with Matplotlib and enhance them with advanced styling capabilities of Seaborn.
• Flask: Introduce the popular web framework Flask for building dynamic web applications with Python.

Week 4: Real-World Applications and Capstone Project

• Data Analysis with Pandas: Apply your Pandas skills to real-world datasets for data cleaning, exploration, and analysis.
• API Development with Flask: Build a simple API using Flask to interact with data and provide services.
• Web Scraping with BeautifulSoup: Extract valuable data from websites using BeautifulSoup and leverage it for analysis or automation.
• Capstone Project: Choose a project that interests you and apply your newly acquired skills to solve a real-world problem using Python.