Course map
Every stage and module in order. Modules that are not written yet say so.
Stage 0: Orientation
Understand what a program is, how exact-match judging works, and how to read an error message.
Stage 1: Python fundamentals
Read and write core Python 3.8 syntax and data types fluently.
M1.1Values, types, variables and
print1 lessonM1.2Integer arithmetic and operators1 lessonM1.3Reading input1 lessonM1.4Booleans and conditionals1 lessonM1.5for loops and range1 lessonM1.6while loops, break/continue, sentinels and EOF1 lessonM1.7Strings1 lessonM1.8Lists (1D and 2D)1 lessonM1.9Tuples, dictionaries and sets1 lessonM1.10Functions and scope1 lessonM1.11Output formatting1 lessonM1.12Floats, precision and big integers1 lessonM1.13Imports and the standard library tour1 lessonM1.14Recursion fundamentals1 lessonM1.15The Python 3.8 language boundary1 lessonStage 2: Problem-solving foundations
Read a problem statement, plan before coding, test deliberately, and debug systematically.
M2.1Reading a CCC problem statement1 lessonM2.2Algorithm-first thinking1 lessonM2.3Simulation1 lessonM2.4Accumulator patterns1 lessonM2.5Brute force and complete search1 lessonM2.6Case analysis and edge cases1 lessonM2.7Testing1 lessonM2.8Debugging1 lessonM2.9Complexity analysis and deriving the target from N1 lesson
Stage 3: Junior J1–J3
Apply loop, string, lookup and grid techniques to early-contest problems.
M3.1Formula-plus-condition problems (J1 pattern)1 lessonM3.2Loop-and-count problems (J2 pattern)1 lessonM3.3String processing I: counting, runs and building1 lessonM3.4String processing II: tokenizing with state1 lessonM3.5Lookup tables1 lessonM3.6Frequency arrays and counting1 lessonM3.7Grid basics1 lessonM3.8Clock and calendar arithmetic, modulo and periodicity1 lessonM3.9Linear-pass thinking and hidden costs of built-ins1 lessonM3.10Fast input and output1 lesson
Stage 4: Junior J4–J5 / Senior S1–S2
Apply hashing, sorting, prefix sums, search patterns and basic graph traversal.
M4.1Hash-based lookup1 lessonM4.2Sorting with keys, and greedy1 lessonM4.3Prefix sums (1D, 2D, prefix/suffix max)1 lessonM4.4Difference arrays and interval clamping1 lessonM4.5Mathematical insight: parity, invariants, closed forms1 lessonM4.6Number theory I1 lessonM4.7Grid transformations1 lessonM4.8Stacks and queues1 lessonM4.9Two pointers and index pointers1 lessonM4.10Backtracking search with pruning1 lessonM4.11Memoization and introductory dynamic programming1 lessonM4.12Graphs I: modelling and adjacency lists1 lessonM4.13BFS and flood fill (iterative)1 lessonM4.14Compressed data and values you cannot expand1 lessonM4.15Circular arrays1 lesson
Stage 5: Senior S3
Apply binary search, hashing, trees, sliding windows and interval techniques.
M5.1Constructive problem solving1 lessonM5.2Pattern discovery by small-case enumeration1 lessonM5.3Sliding windows with counts1 lessonM5.4Hashing: polynomial rolling hash1 lessonM5.5Binary search1 lessonM5.6Convex functions: ternary search and slope sweep1 lessonM5.7Iterative DFS and recursion elimination1 lessonM5.8Trees I: rooting, parent/order arrays, pruning and diameter1 lessonM5.9BFS variants: multi-source, 0-1 BFS, zero-cost moves, reverse graph1 lessonM5.10Disjoint Set Union (union-find)1 lessonM5.11Heaps and lazy deletion; ordered-set substitutes1 lessonM5.12O(N^2) DP on intervals and centre expansion1 lessonM5.13Randomized strategies1 lesson
Stage 6: Senior S4
Apply shortest paths, minimum spanning trees, tree DP, sweep lines and Fenwick trees.
M6.1Dijkstra's shortest paths1 lessonM6.2State-space graph modelling and sparsification1 lessonM6.3Minimum spanning tree: Kruskal plus DSU1 lessonM6.4DFS tree properties1 lessonM6.5Tree DP1 lessonM6.6Interval DP (O(N^3))1 lessonM6.11Monotonic stack and deque1 lessonM6.7Advanced DP design1 lessonM6.8Coordinate compression and sweep line1 lessonM6.9Counting and combinatorics1 lessonM6.10Fenwick tree (Binary Indexed Tree)1 lessonM6.12Doubling and binary lifting on sequences1 lessonM6.13Memoisation over floor-division blocks1 lesson
Stage 7: Senior S5 and advanced
Apply segment trees, advanced dynamic programming and deeper number theory.
M7.4Exchange arguments, scheduling and greedy proofs1 lessonM7.1Segment tree (iterative, custom merge)1 lessonM7.2Lazy propagation1 lessonM7.3Sparse table1 lessonM7.5Probability and expected value1 lessonM7.6Number theory II1 lessonM7.7DP with hash maps (prefix-sum-keyed DP)1 lessonM7.82D range-max DP and doubling on shapes1 lessonM7.9Sqrt decomposition1 lessonM7.10Ad hoc math and geometry optimisation casework1 lessonM7.11Online algorithms and encrypted input1 lessonM7.12Python constant-factor engineering at scale1 lessonM7.13LCA and binary lifting on trees1 lessonM7.14C++ bridge (optional)1 lesson
Stage C: Contest skills
Contest skills that apply across every stage: rules, templates, subtask strategy, time management, testing against a brute force, and reading grader feedback.
C.1CCC rules and integrity1 lessonC.2Using the official Python docs under contest conditions1 lessonC.3Typing templates from memory1 lessonC.4Subtask and partial-marks strategy1 lessonC.5Time management over 3 hours1 lessonC.6Stress testing against a brute force1 lessonC.7Reading Grader feedback and submission discipline1 lessonC.8Output edge cases and special checkers1 lessonC.9Mock contests and upsolving1 lessonC.10Local judging with official test data1 lesson