Python Coding Interview Prep 2026 70+ Real Problems

Master 70+ Python coding interview problems using proven patterns for arrays, trees, graphs and dynamic programming.
What you'll learn

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Solve 70+ Python coding interview problems using practical patterns that transfer to new problems.
Master arrays, strings, hash maps, sets, two pointers and sliding window techniques.
Solve stack, queue, heap, binary search, sorting and interval problems with efficient approaches.
Build and manipulate linked lists, binary trees and binary search trees with confidence.
Solve graph problems using traversal, shortest path and other practical graph algorithms.
Apply backtracking and dynamic programming to solve challenging interview problems.
Recognize common coding interview patterns and choose the right strategy for unfamiliar problems.
Analyze solutions for correctness and time and space complexity.
Requirements

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Basic Python programming knowledge is recommended, including variables, functions, lists and dictionaries.
A Python environment and code editor are recommended for practicing the solutions.
Basic familiarity with common data structures is helpful but not required.
No previous coding interview experience is required.
Description

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Preparing for a Python coding interview is not about memorizing a long list of solutions. It's about learning how to recognize patterns, break down unfamiliar problems and choose an effective approach when the answer is not obvious. This course gives you structured, hands-on practice with 70+ coding interview problems designed to help you become a more confident and systematic problem solver.
You'll work through a carefully structured progression covering
-arrays and strings fundamentals
-hash maps, sets and frequency patterns
-two pointers and sliding window techniques
-stacks, queues and heaps
-binary search, sorting and intervals
-linked lists
-binary trees and binary search trees
-graphs and graph algorithms
-backtracking
-dynamic programming
You'll also tackle practical Python interview patterns involving custom iterators, generators, decorators and an LRU cache.
The focus is not simply on reaching the final answer. You'll learn how to

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approach a problem from the start, identify the underlying pattern, choose the right data structure or technique and build a solution step by step. You'll also consider correctness along with time and space complexity so you can understand not only whether a solution works but whether it is an efficient approach.
The course is designed to build your skills progressively. You'll start with more approachable problems before moving into increasingly challenging questions involving trees, graphs, backtracking and dynamic programming. This gives you the opportunity to develop problem-solving instincts instead of relying on memorized solutions.
Whether you're preparing for a Python coding interview, a technical assessment or a software engineering role, this course gives you a focused way to practice the types of problems that can appear in real interview processes.
By the end, you'll have solved 70+ Python coding problems, practiced the most important problem-solving patterns and built a practical toolkit for approaching unfamiliar coding challenges with greater speed, structure and confidence.
Learn the patterns. Solve the problems. Build interview confidence.
Who this course is for

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Developers preparing for Python coding interviews and technical assessments who want focused, practical preparation.
Python programmers who want to solve real interview problems and develop stronger algorithmic problem-solving skills.
Developers who want to learn reusable problem-solving patterns they can apply to unfamiliar coding challenges.
Students and self-taught developers preparing for software engineering interviews and coding assessments.
Developers who know Python but want to become faster, more confident and more systematic when solving coding problems.
Anyone looking for hands-on Python interview preparation focused on problem solving, patterns and practical solutions.
Homepage

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