DSA for Coding Interviews: Big O and Arrays Course Guide

Data Structures And Algorithms For Interview Preparation is a free course that builds the core DSA skills tested in coding interviews. It is for students and developers who want to analyse code with Big O notation and solve array problems with the techniques interviewers ask about most, such as binary search, sliding window and two pointers.

The course has 29 videos, about 2.9 hours in total, on YouTube. It covers two modules so far: Big O notation and arrays, with C++ set up in Visual Studio Code. This guide explains what each part covers and, importantly, the right order to watch it in. The full list is on the DSA interview course page.

Who this course is for

This is an Intermediate course. It suits you if:

• You can already write basic programs and want to prepare for technical interviews.
• You are a student preparing for campus placements or a developer preparing to switch jobs.
• You find it hard to explain the time and space complexity of your solutions.
• You know arrays exist but want proven patterns for array problems.

Basic programming knowledge is assumed. The course sets up a C++ development environment, so some familiarity with C++ or a similar language will help.

What you will learn

The videos group into five themes.

1. Setup and the language of complexity. Setup C++ Development Environment In Visual Studio Code, Big O Notation Introduction and Understand DSA Greeks give you a working environment and the vocabulary you need to talk about performance.

2. The common complexity classes. Lessons on linear time O(n), dropping constants, quadratic time O(n^2), identifying dominant terms, constant time O(1), logarithmic time O(log n) and exponential time teach you to read a piece of code and estimate how it grows. Interviewers almost always ask about this.

3. Analysing real code. Space Complexity Analysis, Analyzing Nested Loops, Big O for Common Algorithms, Big O for Vector Operations and Summary of Big O Notations Concepts apply the theory to real patterns, so you can justify your answer instead of guessing.

4. Array fundamentals. Introduction to Arrays, Fixed Size vs Dynamic Arrays, Time Complexity of Arrays, Array Operations: Insert, Delete, Update, Memory Layout of Arrays and the guide to multi-dimensional arrays explain how arrays really work in memory and what each operation costs.

5. Array problem-solving techniques. Searching in Arrays: Linear Search, Binary Search, merging arrays, Rotating Arrays, Finding the Maximum Subarray Sum: Kadane’s Algorithm, Sliding Window Technique and Two Pointers Technique are the patterns behind many popular interview questions.

How the course is organised

There are 29 videos, most 3 to 9 minutes long, plus a 26-minute course introduction.

One thing to know: the YouTube playlist is listed in reverse order, newest first. The first video on the playlist is the Two Pointers lesson, and the course introduction is at the end. Follow the lesson numbers in the titles instead:

• Start: Learn Data Structure And Algorithms Step By Step For Interview Preparation - Course Introduction.
• Module 1, Big O Notation: lessons 01 to 15, from the C++ setup to the summary of Big O concepts.
• Module 2, Arrays: lessons 01 to 12, from the introduction to arrays to the two pointers technique. A few array videos without numbers (Master Arrays in Data Structures, multi-dimensional arrays and merging arrays) fit naturally alongside the numbered array lessons.

The course introduction describes a wider plan for the course. The videos published so far cover Big O and arrays.

How to study it step by step

1. Watch the course introduction first, even though it sits at the end of the playlist.
2. Set up C++ in Visual Studio Code with lesson 01 so you can run every example.
3. Go through Big O lessons 02 to 15 in order. After each one, write a short function and state its time and space complexity out loud, as you would in an interview.
4. Move to the array module. Start with the introduction, fixed versus dynamic arrays and the cost of operations before you try any problem-solving technique.
5. For each technique video, pause before the solution, try the problem yourself, then compare. This is especially useful for binary search, Kadane’s algorithm, sliding window and two pointers.
6. Practise explaining. Interviews test how you reason, not only the final code. Explain each solution and its Big O in two or three sentences.
7. Revisit the summary of Big O concepts at the end to tie the two modules together.

The videos are also on YouTube as a playlist. For the rest of your interview preparation, see Interview Fundamentals and Resume and Ace the System Design Interview with Real-World Architectures.

Frequently asked questions

Is this DSA course free?

Yes. All 29 videos are free on YouTube. You can follow them from the course page or the playlist.

Which programming language does the course use?

The course sets up a C++ development environment in Visual Studio Code in its first Big O lesson, and the examples are built from there.

Does it cover linked lists, trees and graphs?

The course introduction describes a wider plan, but the videos published so far cover Big O notation and arrays only. Use them to build a strong base before moving on to other data structures.

How long does it take to finish?

The videos total about 2.9 hours. If you try every problem yourself before watching the solution, plan for one to two weeks of regular practice.