Sliding Window Coding Patterns: From Novice to Ninja

Master efficient coding patterns using Swift. Solve real-world problems with fixed and dynamic sliding windows.

What you'll learn
- Understand the fundamentals of the sliding window technique in algorithm design.
- Identify scenarios where fixed-size sliding windows are the optimal solution.
- Implement efficient solutions to classic sliding window problems in Swift.
- Analyze the time and space complexity of sliding window algorithms.
- Differentiate between fixed-size and variable-size sliding window strategies.
- Apply sliding window patterns to solve real-world coding challenges like max sum, averages, and pattern detection.
- Use Swift collections such as dictionaries, sets, and queues to maintain state in sliding windows.
- Write reusable, testable, and performance-oriented Swift functions for window-based problems.
- Debug and optimize window-based solutions using step-by-step logic and test cases.
- Develop confidence to tackle interview questions that require sliding window solutions.

Requirements
- A basic understanding of programming concepts (variables, loops, conditionals).
- Familiarity with Swift syntax and functions.
- Ability to work with Swift arrays and dictionaries.
- Understanding of control flow (if/else, for/while loops).
- Some exposure to writing functions and using parameters in Swift.
- Access to a Mac or a Swift-compatible coding environment (e.g. Xcode, Playgrounds).
- Willingness to learn algorithmic thinking and problem-solving techniques.
- Comfort reading and writing simple Swift functions in a code editor.
- No prior experience with data structures or algorithms is required, but helpful.
- Motivation to practice and refine logic through guided coding challenges.

Description
Are you a Swift developer looking to level up your algorithmic skills and crack real-world coding challenges? This course is your focused guide to mastering one of the most powerful techniques in problem-solving: thefixed-size sliding window.

Sliding window algorithms are essential for solving problems that involve subarrays, sequences, or contiguous chunks of data. They're common in technical interviews, coding competitions, and practical development scenarios — yet many developers struggle to implement them efficiently and confidently. This course changes that.

In"Sliding Window Coding Patterns: From Novice to Ninja", you'll learn how to:

Identify problems that require fixed-size window solutions

Apply efficient window logic using Swift arrays, dictionaries, and queues

Optimize performance by maintaining state across sliding windows

Write reusable and concise Swift functions for sliding window problems

This course includes real coding challenges that walk you through problems like:

Finding maximum/minimum sums in a window

Calculating averages of subarrays

Tracking frequencies and detecting patterns

Identifying unique or repeating values in fixed windows

Each lesson is hands-on, with step-by-step explanations and clear illustrations of how the sliding window is formed, moved, and analyzed.

If you already know basic Swift programming and want to build real algorithmic muscle — especially for interviews or personal growth — this course will help you gain clarity and confidence, one window at a time.

Who this course is for:
- Aspiring iOS developers preparing for technical interviews.
- Swift programmers looking to strengthen their algorithm skills.
- Computer science students learning common coding patterns and techniques.
- Self-taught developers seeking structured problem-solving practice.
- Beginner and intermediate coders who know Swift but struggle with algorithm design.
- Bootcamp graduates aiming to sharpen their data structure and algorithm knowledge.
- Developers transitioning into mobile development using Swift.
- Competitive programming enthusiasts who want to master the sliding window technique.
- Interview candidates preparing for coding rounds at tech companies.
- Educators or tutors looking for ready-made examples to teach algorithmic thinking.
More Info