DSA & Problem Solving

Full outline

Data structures and algorithms organised by problem pattern rather than by topic, so you learn to recognise which technique a new problem wants — plus a realistic practice schedule.

1. 01Data Structures

   Know the cost of every operation.

   • Arrays & strings

     The foundation, and the source of most interview questions.

   • Hash maps & sets

     The single most useful structure in practical problem solving.

   • Linked lists, stacks & queues

     Pointer manipulation and the structures built from it.

   • Trees, heaps & tries

     Hierarchical data and priority access.

   • Graphs

     More problems are graph problems than look like graph problems.

2. 02Problem Patterns

   Recognise the shape and the solution follows.

   • Two pointers & sliding window

     Turning O(n²) scans into O(n) passes.

   • Binary search

     Not just on arrays — on any monotonic answer space.

   • Recursion & backtracking

     Explore the decision tree, prune aggressively.

   • Dynamic programming

     The topic people fear. It is just recursion plus a cache, made systematic.

   • Greedy & intervals

     Locally optimal choices that provably work — and proving that they do.

3. 03Practice System

   Consistency beats intensity.

   • A realistic schedule

     Two focused problems a day for six months beats twelve problems one weekend.

   • Complexity analysis

     Stating time and space cost correctly, every time, without prompting.

   • Mock interviews

     Solving alone and solving while explaining are different skills.