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STUDENTS, GRADUATES AND DEVELOPERS PREPARING FOR TECHNICAL INTERVIEWS

Data Structures and Algorithms

A 10-week program to master problem solving for coding rounds and real engineering work

Help you think through a problem, pick the right data structure, write clean and correct code, and explain its complexity. You practise every day and finish with timed mock coding rounds.

Arrays + StringsTrees + GraphsDynamic programmingInterview practice

Fees and upcoming batch dates are shared in the demo class.

10 weeks
Recommended duration
6 hours
Study time per day
5 days
Training days per week
300 hours
Total duration

OVERVIEW

What this program is about

Build strong problem-solving foundations. Learn the core data structures, reason about time and space, and practise coding-round problems every day until patterns become familiar.

One project, start to finish

Each week adds a new family of problems on top of the last. You keep a personal problem journal and a GitHub repository of solutions, so you can revise patterns before any interview.

How your time is spent

  • 25 Concepts
  • 55 Problem practice
  • 20 Mock rounds and reviews

A typical 6-hour day

  • Concept / instructor session1.5h
  • Guided problem solving1.5h
  • Independent practice2.0h
  • Code review and optimisation0.5h
  • Revision and discussion0.5h

CURRICULUM

10 steps from basics to a finished project

Each step ends with something you can show. Open a step to see what you will cover.

  1. Week 1Problem Solving Foundations

    How to approach a problemBig O notationtime and space trade-offsreading constraintstesting with edge casessetting up the coding environment

    You deliver: Complexity cheat sheet

  2. Week 2Arrays and Strings

    Traversal and in-place updatestwo pointerssliding windowprefix sumsstring manipulationcommon interview patterns

    You deliver: Array and string pattern notes

  3. Week 3Hashing and Sorting

    Hash maps and setsfrequency countinganagram and subarray problemssorting algorithmsbinary search and its variations

    You deliver: Hashing and searching solutions

  4. Week 4Linked Lists, Stacks and Queues

    Singly and doubly linked listsreversal and cycle detectionstacks for parsingmonotonic stackqueues and deques

    You deliver: Core structures implemented from scratch

  5. Week 5Recursion and Backtracking

    Recursion tree thinkingbase casessubsets and permutationsbacktracking with pruningmemory and call stack

    You deliver: Backtracking problem set

  6. Week 6Trees and Binary Search Trees

    Tree traversalsheight and diameterlowest common ancestorBST insert and searchtree construction problems

    You deliver: Tree problem set with tests

  7. Week 7Heaps and Priority Queues

    Heap operationstop-K problemsmerging sorted listsscheduling problemsintervals

    You deliver: Heap and interval solutions

  8. Week 8Graphs

    Adjacency list and matrixBFS and DFSconnected componentstopological sortDijkstraunion-find

    You deliver: Graph algorithm library

  9. Week 9Dynamic Programming and Greedy

    Memoisation and tabulationone and two dimensional DPknapsack and subsequence patternsgreedy choice proofs

    You deliver: Dynamic programming pattern notes

  10. Week 10Mock Rounds and Final Review

    Timed coding roundsexplaining solutions aloudoptimising a working solutionrevision planusing AI to review your code

    You deliver: Two mock round reports

AFTER THE COURSE

Skills you will have

Practical skills you will have used on your own project, not just read about.

  • Big O time and space analysis
  • Arrays, strings and two-pointer patterns
  • Hash maps and sets
  • Sorting and searching algorithms
  • Linked lists, stacks and queues
  • Heaps and priority queues
  • Binary trees and binary search trees
  • Graph traversal (BFS and DFS)
  • Shortest paths and union-find
  • Recursion and backtracking
  • Dynamic programming
  • Greedy algorithms
  • Clean coding and unit tests for solutions
  • Communicating a solution in an interview

CAREERS

Roles you can apply for

Job titles this curriculum prepares you for. They are examples, not a promise of placement.

ASSESSMENT

How your progress is judged

Your work on the project is what counts. Each area carries a share of the final result.

  • Complexity analysis10%
  • Arrays, strings and hashing15%
  • Linked lists, stacks and queues10%
  • Trees and binary search trees15%
  • Graphs10%
  • Recursion and dynamic programming15%
  • Mock coding round 110%
  • Mock coding round 2 and final review15%

OUTCOMES

What you will be able to do

  • Analyse time and space complexity using Big O
  • Choose the right data structure for a given problem
  • Solve array, string and hashing problems with common patterns
  • Implement and use linked lists, stacks, queues and heaps
  • Traverse and modify trees and binary search trees
  • Solve graph problems with BFS, DFS and shortest-path methods
  • Break problems into subproblems with recursion and dynamic programming
  • Write clean, tested code under a time limit
  • Explain your approach and trade-offs clearly in an interview
  • Use AI tools to check ideas without replacing your own thinking

PORTFOLIO

What you finish with

  • Personal problem journal with pattern notes
  • GitHub repository of solutions with tests
  • Complexity cheat sheet
  • Implementations of core data structures from scratch
  • Graph algorithm library
  • Dynamic programming pattern notes
  • Two timed mock coding round reports
  • Final revision plan

FROM OUR BLOG

Articles about Data Structures and Algorithms

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Ready to start building?

Enrol to register your interest, or book a free demo class. Fees and batch dates are shared by our team.

Data Structures and Algorithms