Data Structures & Algorithms Roadmap

Overview

This lecture provides a beginner-friendly roadmap to learning data structures and algorithms, focuses on key resources, study tips, and steps to prepare for technical interviews.

Why Learn Data Structures & Algorithms

• Data structures and algorithms (DSA) are crucial for software engineering interviews and career growth.
• Not having DSA knowledge can limit job opportunities and career advancement.
• Practice and consistency are more important than innate math skills.

Getting Started with DSA

• Start with a high-level overview of core concepts (data structures, algorithms, Big O, recursion, pointers).
• Big O notation is essential—learn to analyze time and space complexity of code.
• Learning resources: YouTube channels like freeCodeCamp and Bro Code offer good introductions.

Recommended Study Materials & Courses

• For beginners, use books with diagrams and simple explanations (the recommended book explains Big O and binary search clearly).
• Complete an online course for structure; recommended: Zero to Mastery, CS50, or Colt Steele’s Udemy course.
• Follow a structured path from basic concepts to advanced data structures.

Practice Strategies

• Build basic data structures (like linked lists, arrays) from scratch and memorize their implementation.
• Memorization is beneficial for interviews, especially for core data structures.
• Calculate Big O by understanding, not memorizing.

Coding Practice and Problem Solving

• Start problem solving on platforms like Codewars (easier problems) before moving to LeetCode.
• Regular practice sharpens logic and problem-solving skills.
• Begin every coding session with a practice problem and gradually increase difficulty.
• Use AI tools like ChatGPT for coding help and optimization suggestions.

Intermediate/Advanced Learning Resources

• For deeper knowledge, use comprehensive books (can be dry but thorough).
• Helpful YouTube channels: Abdul Bari, Rob Edwards, Bro Code.
• Focus on core algorithms (e.g., merge sort, quick sort); don't try to learn every variation.

Study Mindset and Progress

• Efficient, focused study (e.g., “blind 75” problems) is more effective than trying to master everything.
• Celebrate small milestones and keep learning enjoyable.
• DSA is a lifelong, high-value skill for tech careers.

Key Terms & Definitions

• Data Structure — a way to store and organize data efficiently.
• Algorithm — a step-by-step procedure for solving a problem.
• Big O Notation — describes the efficiency of an algorithm as input size increases.
• Recursion — a function that calls itself to solve a smaller instance of a problem.
• Pointers — variables that store memory addresses, used in data structures like linked lists.

Action Items / Next Steps

• Watch an introductory DSA video (e.g., freeCodeCamp).
• Read a beginner-friendly DSA book, focusing on Big O and binary search.
• Enroll in a recommended online course.
• Practice building data structures from scratch.
• Start solving beginner problems on Codewars, then progress to LeetCode.
• Use AI tools for feedback and optimization.
• Prepare for the next lecture focused on LeetCode strategies.