Data Structures & Algorithms

Online self-study + projects. Strengthen problem-solving with arrays, trees, graphs, and complexity analysis.

Data Structures & Algorithms

Course Overview

Master the fundamentals behind efficient code. Implement core data structures and algorithms in practice, analyze time and space complexity, and apply repeatable patterns to solve real problems. You’ll practice with guided sets and build a small “algorithm toolkit” you can reuse in interviews and projects.

What You’ll Learn

  • Complexity analysis and Big-O reasoning
  • Arrays, strings, and linked lists in practice
  • Stacks, queues, and hash tables
  • Trees & graphs with BFS/DFS traversal
  • Sorting and searching algorithms
  • Greedy, two-pointers, and sliding window patterns
  • Dynamic programming (intro) and memoization
  • How to structure and communicate solutions in interviews

Topics Covered

  • Asymptotic notation (Big-O, Ω, Θ)
  • Arrays & strings techniques
  • Linked lists (SLL, DLL)
  • Stacks & queues
  • Hash maps/sets & collisions
  • Trees: traversal & properties
  • Binary search trees
  • Heaps & priority queues
  • Graph representations (adjacency list/matrix)
  • BFS/DFS, topological sort (intro)
  • Sorting (quick/merge/heap)
  • Binary search & variants
  • Greedy strategies & proofs (intuition)
  • Two-pointers & sliding window
  • Intro to dynamic programming
  • Project: “Algo Toolkit” library

Who Is This For?

Developers with basic coding experience who want stronger problem-solving skills for technical interviews, competitive programming, or writing more efficient production code.

FAQs

Comfort with a programming language (Python/JS/Java, etc.) and basic data types, loops, and functions.

Examples are provided in Python and JavaScript, but the concepts are language-agnostic. Use whichever you prefer.

Need help choosing a path?

Tell us your goals and we’ll recommend the right sequence of courses.

Talk to Us