Python Data Structures and Algorithms for Coding Interviews

Preparing for technical coding interviews can feel overwhelming without a structured approach to problem-solving. Understanding how to choose and implement the right data structures and algorithms is the key to writing efficient code and passing competitive technical assessments. This text-based course guides you through the fundamental concepts of computer science using Python. You will transition from writing basic scripts to designing highly optimized, production-ready algorithms, giving you the confidence to tackle challenging technical interview questions. What you'll learn: - Understand the foundational principles of Big O notation to analyze time and space complexity. - Implement essential data structures from scratch, including linked lists, stacks, queues, trees, and graphs. - Apply modern Python features like type hints and dataclasses to write clean, self-documenting algorithmic code. - Master key algorithmic paradigms such as recursion, binary search, sorting, greedy algorithms, and dynamic programming. - Solve common coding interview problems systematically by breaking down complex requirements into structured code. - Practice verifying your solutions using clean coding standards and basic testing principles. You will begin by learning core vocabulary, algorithmic complexity, and basic memory management before moving on to hands-on implementation of linear and non-linear data structures. Each concept is reinforced with written explanations, step-by-step code walkthroughs, and practical exercises designed to simulate real-world technical interviews. This course is designed for beginner to intermediate Python programmers who want to strengthen their computer science foundations and prepare for technical job interviews. No prior computer science degree or advanced mathematical background is required. Start building a strong algorithmic foundation and take the next step in your software engineering career today.