> cs·fundamentals
interview 0% an interactive refresher
01 [I][A] Stage 1

Core CS / DSA

Big-O, the structures worth knowing, graphs, and pattern recognition — practical fluency, not from-scratch implementation.

chapters
6
objectives
33
core
22
est. time
2h 30m
  1. 01
    1.1 Big-O & complexity reasoning ★ core

    Big-O describes how runtime/space grows as input grows. Master the ordering of the common classes and the difference between best/average/worst and amortized cost.

    4 objectives · 2 readings · 25m
  2. 02
    1.2 Linear structures — when to reach for each ★ core

    Arrays, dynamic arrays, linked lists, stacks, queues, deques — know the access/insert/delete costs and the one-sentence “use it when” for each.

    7 objectives · 1 readings · 25m
  3. 03
    1.3 Hashing structures ★ core

    Hash maps/sets give average O(1) by key. Understand collisions, load factor/rehash, and when a hashmap is the wrong tool (ordering / range queries).

    5 objectives · 22m
  4. 04
    1.4 Trees

    BSTs, self-balancing trees, B/B+ trees (why DB indexes use them), tries, and heaps. The B-tree item directly feeds the Databases indexes chapter.

    6 objectives · 1 readings · 28m
  5. 05
    1.5 Graphs

    Vocabulary, adjacency list vs matrix (sparse vs dense), and BFS vs DFS — when to use each.

    5 objectives · 20m
  6. 06
    1.6 Algorithm categories — recognize the pattern ★ core

    Interviews test pattern recognition: sorting tradeoffs, binary search, two pointers/sliding window, recursion, divide-and-conquer/greedy/DP. Aim for recognition speed.

    6 objectives · 2 readings · 30m

Section assessment

Harder, multi-concept questions drawn from across the module. Aim for 75%.

section assessment12 questions · pass ≥ 75%
  1. 01hard

    DP applies when a problem has overlapping subproblems AND…

  2. 02medium

    An O(n²) algorithm takes 1s on 1,000 items. Roughly how long on 10,000 items?

  3. 03medium

    BFS over a graph naturally uses which structure to track the frontier?

  4. 04medium

    You need to keep keys in sorted order AND do range queries. A hash map is wrong because…

  5. 05medium

    Exceeding a hash table's load factor triggers a resize/rehash.

  6. 06medium

    Why do relational database indexes use B-trees / B+ trees?

  7. 07medium

    You need the top-K largest items from a stream. Best structure?

  8. 08medium

    For a SPARSE graph, which representation is more memory-efficient?

  9. 09medium

    Shortest path in an UNWEIGHTED graph is found by:

  10. 10medium

    “Longest substring without repeating characters” is a classic case of:

  11. 11medium

    Comparison-based sorts are bounded below by:

  12. 12medium

    You keep adding edges and repeatedly ask “are these two nodes connected yet?” Best tool?