Learning path

Data Structures and Algorithms Roadmap

DSA in the order it is actually learned: build each data structure yourself, then the sorts, then recursion, dynamic programming and graphs, then a bank of interview problems to prove it. Pick Python, Java, C++, Go or any of thirteen languages - nearly every course ships in all of them. Free, in your browser, with a certificate on most courses.

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421 lessons228 challenges702 quiz questions

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The data structures and algorithms path, step by step

41 courses421 lessons228 challenges702 quiz questions

Each step is a set of existing Coddy courses. Take them in order, or jump into the one you are missing - your progress is saved per course either way, and most courses are taught in up to thirteen languages.

1
Step 1
Data Structures Series, part one
Start this stepStartStack, queue, binary tree, hash table and linked list, each built from scratch and then used to solve problems. The five structures behind most interview questions and most of the standard library you already use.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. The structures that separate a candidate who memorised a list from one who can pick the right tool for a problem.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, compared and watched in the visualizer. Sorting is where Big-O stops being notation and becomes something you can see.Start
8 courses, in order
74 lessons31 challenges319 questions
4
Step 4
Recursion, dynamic programming, bits
Start this stepStartRecursive thinking through a bank of challenges, then dynamic programming (in Python) from memoisation to tabulation, then bit manipulation (in C++). Recursion is the idea the next two depend on, which is why it comes first.Start
3 courses, in order
47 lessons15 challenges
5
Step 5
Graph algorithms
Start this stepStartBreadth-first and depth-first search, Dijkstra, Bellman-Ford, topological sort, Kruskal and Prim - one focused course each, on the graph structure you built in step two.Start
7 courses, in order
63 lessons21 challenges383 questions
6
Step 6
Interview practice
Start this stepStartTen interview challenge packs, the Python interview series and two coding-problem banks: unfamiliar problems, graded by test cases, solved without a tutorial. This is the step that turns the previous five into an offer.Start
13 courses, in order
99 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 on Coddy

You build every structure, in your language. The stack, the linked list, the hash table and the AVL tree are implemented from scratch and then used, in whichever of thirteen languages you interview in - not read about in one and translated later.
The sorts, watched and written. Each sorting course pairs with Coddy's algorithm visualizer, so you see why merge sort divides and why quick sort partitions before you write the code that does it.
Interview-shaped from the first course. Every lesson ends in a graded challenge with test cases, the shape of a technical interview question, and the path ends with ten challenge packs and two problem banks solved without a tutorial.
AI hints that read your solution. When a test case fails or a recursion never returns, Bugsy looks at what you wrote and nudges you toward the fix without handing over the answer. A free certificate on most courses (24 of the 41), each verifiable at its own URL.

Frequently asked questions about learning data structures and algorithms

In what order should I learn data structures and algorithms?

Linear structures first (stack, queue, linked list), then hash tables and trees, then the sorts, then recursion as a way of thinking, then dynamic programming and graphs, and only then a steady diet of interview problems. Problems before structures is the mistake most self-taught learners make: you cannot recognise that a question wants a heap if you have never built one. That is this path, in that order.

Which language is best for DSA?

The one you will interview in. Python is the fastest to write and what most people choose; Java and C++ are what many large companies and competitive programmers use; Go and Rust are increasingly accepted. The data structures, sorting, graph and interview-pack courses are taught in thirteen languages with the same lessons and test cases (dynamic programming and the Python interview series are Python only, bit manipulation is C++), so pick one and, if a job asks for another, repeat a course in it - the second time takes days.

Is this path enough for coding interview prep?

It is the material every technical interview draws on, taught by building it, plus the practice: ten interview challenge packs, a Python interview series and two coding-problem banks at the end. What it does not replace is volume - after the path, keep solving unfamiliar problems on a timer, and treat system design as a separate study. Most junior and mid-level loops are covered by what is here.

How long does it take to learn data structures and algorithms?

Around three to four months at an hour a day for the whole path: three to four weeks for the first five data structures, three for the next five, two to three for the sorts, three for recursion, dynamic programming and bit manipulation, two to three for the graph algorithms, and the interview packs as long as you keep going. Dynamic programming is where people slow down; the recursion course before it is what makes it click.

Do I need math to learn algorithms?

Less than you fear. You need to be comfortable with logarithms (to read Big-O), basic counting, and the idea of a proof by induction, which is what recursion teaches in practice. No calculus, no linear algebra. If you can follow why binary search halves the problem each step, you have the mathematics this path needs.

Is the DSA course free?

Every course on the path is free: the lessons, the in-browser editor, the test cases, the AI hints and the certificates on the courses that issue one. Pro removes the daily energy limit and adds unlimited AI help; nothing on this page is locked behind it.

Are data structures still worth learning now that AI writes code?

More than before. Interviews still test them because they are the fastest way to tell whether someone can reason about a program rather than prompt for one. On the job, the person who knows a hash lookup is constant time and a nested loop is not is the person who can read what the AI produced and say whether it will survive ten million rows.

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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