Grokking the Art of Recursion for Coding Interviews

Why start with recursion

Recursion sits underneath three of the hardest interview topics: trees, graphs and dynamic programming. People who find all three difficult often do not have three problems. They have one: they do not trust a recursive function enough to write it without tracing every call.

What it covers

The course page lists 4 chapters, 44 lessons, 52 playgrounds and a stated 30 hours of study time (September 2026).

• Introduction (6 lessons): what recursion is, the types of recursion (linear, tail, binary, multiple and indirect), recursion versus iteration, the two strategies that build on it (divide and conquer, and dynamic programming through memoization and tabulation), and complexity analysis of recursive functions including stack space.
• Easy problems: basic sum, factorial, greatest common divisor, decimal to binary, prime check, perfect square, number frequency.
• Medium problems: Pascal's triangle, binary search, inserting into a BST, BST inorder traversal, merge sort, quick sort, depth first search, removing nodes from a linked list.
• Hard problems: Fibonacci with memoization, Good Number, Split BST and Pow(x, n).

Each of the 19 problems has a diagram, full solution and complexity analysis, in Python, Java, C++, JavaScript, Go and C#.

What to do afterwards

Once recursion feels natural, the next steps in the same library build directly on it: the subsets and backtracking chapters of Grokking the Coding Interview, then Grokking Tree Coding Patterns for Interviews and Grokking Dynamic Programming Patterns for Coding Interviews.

Is it worth it?

As of September 2026 the course page lists a one-time price of $58 for lifetime access, and it is included in the provider's all-courses subscription. It shows a 4.8 rating from about 7,800 ratings, the highest in this group of courses.

The course suits people who want a gentle, ordered progression with diagrams, from simple arithmetic recursion through to the recursive algorithms interviews actually use.

How long it really takes

Thirty hours is the stated figure, but the content is short; most learners who practise each problem finish in one to two weeks at an hour a day.

How to use it well

• Stop tracing. Write the recursive case assuming the function already works for smaller inputs (the "leap of faith"), and check only the base case and one small example. Getting comfortable with that is the goal.
• Draw the recursion tree for merge sort and Fibonacci once, by hand. It makes both complexity and memoization obvious.
• Rewrite binary search and DFS iteratively after the recursive versions, to see what the call stack was doing for you.
• Move on to backtracking straight afterwards while the ideas are fresh.

Common questions

Is it for beginners? Yes, for programming beginners who know functions and basic data types. The easy chapter starts very gently.

Will it help with dynamic programming? Yes, it lays the foundation (memoized Fibonacci, complexity of recursion), and Grokking Dynamic Programming Patterns for Coding Interviews builds directly on it.

Best for: self-taught engineers and students who avoid recursive solutions on instinct.