Learning path

Data Structures and Algorithms in C++

Q: Which STL containers match which data structures?

std::vector is a dynamic array, std::stack and std::queue are adaptors over std::deque by default, std::list is a doubly linked list, std::unordered_map and std::unordered_set are hash tables, std::priority_queue is a binary heap (a max-heap by default, unlike Python's and Java's), and std::map and std::set are balanced binary search trees, in practice red-black trees. There is no trie or graph container; you write those.

Q: Do I need to know C++ before starting this path?

Classes, pointers, references and std::vector, at least. If those are new, Coddy's C++ course covers them first, free, and this path picks up where it ends.

The STL is this path in library form: std::vector, std::unordered_map, std::priority_queue and std::set are a dynamic array, a hash table, a heap and a balanced tree. Build each one in C++ with classes and pointers, then use the STL knowing what every call costs. Bit manipulation is taught in C++ itself. Free, in your browser, with a certificate on most courses.

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394 lessons228 challenges702 quiz questions

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DSA in C++, step by step

39 courses394 lessons228 challenges702 quiz questions

Each step is a set of existing Coddy courses, and every Start button opens them in C++. The two courses not taught in C++ yet are listed after the steps.

1
Step 1
Data Structures Series, part one
Start this stepStartStack, queue, binary tree, hash table and linked list, each built from scratch in C++ with classes and pointers, then used to solve problems. After it, std::stack, std::queue and std::unordered_map are structures you have written.Start
5 courses, in order
66 lessons34 challenges
2
Step 2
Data Structures Series, part two
Start this stepStartDoubly linked list, heaps and priority queues, tries, graphs and the self-balancing AVL tree. std::priority_queue is a max-heap by default, where Python's and Java's heaps are min-heaps; once you have written one, flipping it with std::greater is obvious.Start
5 courses, in order
72 lessons42 challenges
3
Step 3
Sorting algorithms
Start this stepStartBubble, selection, insertion, merge, quick, heap, counting and radix sort, written in C++ and watched in the visualizer. std::sort is usually an introsort, quicksort that falls back to heapsort, and std::stable_sort a merge sort; this step is why those choices make sense.Start
8 courses, in order
74 lessons31 challenges319 questions
4
Step 4
Recursion and bit manipulation
Start this stepStartRecursion challenges and bit manipulation, both in C++, the language the bit manipulation course is written for. Dynamic programming is taught in Python and listed after the steps; its memo tables translate straight to std::vector.Start
2 courses, in order
1. Recursion Challenges - Master The Recursive Thinking15 lessons15 challenges
2. Bit Manipulation17 lessons
32 lessons15 challenges
5
Step 5
Graph algorithms
Start this stepStartBreadth-first and depth-first search, Dijkstra, Bellman-Ford, topological sort, Kruskal and Prim in C++, on the graph you built in step two. Dijkstra's priority queue is std::priority_queue with std::greater: the heap from step two, in library form.Start
7 courses, in order
63 lessons21 challenges383 questions
6
Step 6
Interview practice
Start this stepStartTen interview challenge packs and two coding-problem banks, all twelve in C++ and graded by test cases: unfamiliar problems, solved without a tutorial. The Python interview series, Python only, is listed after the steps.Start
12 courses, in order
87 lessons85 challenges

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Intro to Variables

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A variable is a named container that stores a value you can reference later in your program.

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Why learn DSA in C++ on Coddy

The language of competitive programming. Most competitive programmers write C++, for its speed and the STL, and it is accepted in almost every coding interview. Learning DSA in C++ is learning the dialect contests are written in.
Pointers you can see. A linked list in C++ is nodes and pointers, an AVL rotation is a handful of pointer moves, and a destructor frees what you allocated. You learn the structures the way the machine stores them, then let the STL do it for you.
Bit manipulation in its own language. The path's bit manipulation course is taught in C++, so here it is not a detour: masks, shifts and bit tricks come in the language you are already writing. Only dynamic programming and the Python interview series are not: they are taught in Python and listed after the steps.
Graded like an interview. Every lesson ends in a C++ challenge checked by test cases, and when one fails, Bugsy reads your code and nudges you toward the fix without handing over the answer. A free certificate on most courses, each verifiable at its own URL.

Frequently asked questions about DSA in C++

Is C++ good for data structures and algorithms?

It is the most common choice for competitive programming and a strong one for interviews: fast, with a standard library that covers almost every structure you need. The cost is more code and more ways to go wrong, from dangling pointers to invalidated iterators. Building the structures yourself first, as this path does, is how those stop being surprises.

Which STL containers match which data structures?

std::vector is a dynamic array, std::stack and std::queue are adaptors over std::deque by default, std::list is a doubly linked list, std::unordered_map and std::unordered_set are hash tables, std::priority_queue is a binary heap (a max-heap by default, unlike Python's and Java's), and std::map and std::set are balanced binary search trees, in practice red-black trees. There is no trie or graph container; you write those.

Should I implement data structures myself or just use the STL?

Both, in that order. Implement each structure once, so you know why std::unordered_map lookups are constant time on average and why std::map keeps its keys sorted, then use the STL everywhere after. In a contest or an interview nobody expects a hand-written red-black tree; they expect you to choose the right container and know its cost.

C++ or Python for DSA?

C++ if you plan to do competitive programming or interview where it is expected; Python if you want the shortest path from idea to working code. The algorithms are identical, so many people learn in one and compete in the other. Every data structure course on this path is taught in both.

Which courses on this path are not taught in C++?

Two: dynamic programming and the Python interview series, both taught in Python. They are listed after the steps, with a link that opens them in Python. The ideas carry over unchanged: in C++, a memo table is a std::vector or a std::unordered_map.

Do I need to know C++ before starting this path?

Classes, pointers, references and std::vector, at least. If those are new, Coddy's C++ course covers them first, free, and this path picks up where it ends.

Other learning paths

The same courses, arranged for a different role. Progress carries over: a course finished on one path counts on every path that includes it.

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