Advanced8-10 hours

Data Structures & Algorithms: Advanced

The harder algorithmic techniques — heaps, intervals, backtracking, dynamic programming, and greedy — plus a capstone on decomposing and solving genuinely hard problems under real constraints.

What You'll Learn

AlgorithmsDynamic ProgrammingProblem SolvingRecursion

Prerequisites

• Data Structures & Algorithms: Foundations

Learning Outcomes

✓Use heaps for top-K, merge-K, and running-median problems
✓Sweep and merge intervals cleanly
✓Structure backtracking for permutations, subsets, and search
✓Build dynamic-programming solutions from 1D to 2D to interval DP
✓Know when greedy is provably correct — and when it quietly fails
✓Approach an unfamiliar hard problem with a repeatable, systematic method

Course Modules

1hands-on75 minutes

Heaps & Priority Queues

Top-K, merge-K, and running median with heapq

2hands-on60 minutes

Intervals

Merge, insert, and count overlaps with the sort-then-sweep pattern

3hands-on90 minutes

Recursion & Backtracking

Permutations, combinations, subsets, and word search without losing the thread

4hands-on120 minutes

Dynamic Programming

The most-feared topic, made approachable: 1D to 2D to interval DP, with cache-powered memoization

5hands-on60 minutes

Greedy Algorithms

Interval scheduling and jump-game patterns — and how to tell when greedy is actually correct

6project75 minutes

Solving Hard Problems Under Constraints

A repeatable method for unfamiliar problems: decompose the unknown, time-box exploration, reason from examples, and debug under pressure

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