Python — Advanced Data Structures & Problem Solving ( part2/semester 2)

Course Description:
This second-semester course builds on the programming and logical-thinking foundation developed in Python Core Logic & Problem Solving.

Students move beyond basic Python syntax and learn how to organize information, choose appropriate data structures, design better solutions, and solve increasingly challenging programming problems.

The course introduces object-oriented programming (OOP), core data structures, algorithmic thinking, and structured problem solving. The emphasis is on understanding how to approach a problem, not simply writing code that works.

Through guided practice and independent challenges, students develop the technical depth and problem-solving skills needed for advanced programming, competitive coding, AI, robotics, and future computer science courses.

Note: This course covers the second half of the Python curriculum and is designed to be taken after Python Core Logic & Problem Solving (Part 1).

🔹 What Students Will Learn

1. Object-Oriented Programming (OOP)

Students learn how to organize larger programs using classes and objects.

• Classes and objects

• Constructors and instance variables

• Methods and encapsulation

• Abstraction

• Inheritance and polymorphism

• Designing clean, modular, and reusable code

2. Core Data Structures

Students learn how different ways of organizing data can make problems easier to solve.

• Strings — slicing, formatting, parsing, and pattern-based problems

• Lists — traversal, searching, sorting, and nested lists

• Sets — uniqueness, membership testing, and set operations

• Dictionaries — key-value modeling, counting, and frequency maps

• Choosing the right data structure for a given problem

The goal is not just to learn each data structure, but to understand when and why to use it.

3. Problem-Solving & Algorithmic Thinking

Students develop a systematic approach to solving programming problems:

• Understanding and breaking down a problem

• Identifying important information and patterns

• Developing a step-by-step solution

• Choosing appropriate data structures

• Translating ideas into code

• Testing and debugging solutions

• Improving inefficient approaches

Students gradually move from straightforward exercises to multi-step programming challenges.

4. Structured Coding Practice

Students regularly solve coding problems that require them to apply multiple concepts together.

Practice focuses on:

• Logic and reasoning

• Code tracing

• Searching and counting

• Sorting and organization

• Data modeling

• Pattern recognition

• Debugging

• Writing clear and maintainable solutions

5. From “Writing Code” to “Solving Problems”

The focus shifts from learning individual Python features to answering a more important question:

Given a problem, how do I figure out what to do?

Students learn to think through a problem before coding, compare different approaches, and explain why a solution works.

🔹 Learning Style

• Hands-on coding in every class

• Guided examples followed by independent problem solving

• Progressive difficulty from foundational exercises to multi-step challenges

• Frequent debugging and code-tracing practice

• Emphasis on thinking before coding

• Algorithms and data structures introduced as tools for solving problems

If time permits, selected Python game projects may be used to reinforce programming concepts and provide an additional creative application of the skills students have learned.

🔹 Key Outcomes

By the end of Part 2, students will be able to:

✅ Design and use Python classes and objects
✅ Work confidently with strings, lists, sets, and dictionaries
✅ Choose appropriate data structures for different problems
✅ Break down unfamiliar problems into manageable steps
✅ Solve increasingly challenging programming problems independently
✅ Trace, test, debug, and improve their own code
✅ Write cleaner, more organized, and reusable Python programs
✅ Develop a strong foundation for advanced algorithms and computer science

🚀 Where Students Can Go Next

After completing the two-part Python pathway, students can continue in different directions depending on their interests:

Python Core Logic & Problem Solving
↓
Python Data Structures & Problem Solving
↓
Advanced CS / AI / Robotics / Competitive Programming

Students interested in competitive programming can transition into C++ and USACO-focused training, while students interested in AI or robotics can apply their Python foundation to more specialized projects and courses.

See Part I: Python Core Logic & Problem Solving

Note: This curriculum includes both Part 1 and Part 2 content,