Algorithms and Data Structures

What you will learn

• Big O analysis
• Binary search
• Sorting algorithms
• Stacks and queues
• Linked lists
• Hash maps
• Two pointers and sliding windows
• Trees and graphs
• Interview problem solving

Lessons

1. 1

   Big O

   Count the work your code does, name its growth rate, and spot the hidden loops inside everyday Python operations.

   8 exercises

2. 2

   Searching and Sorting

   Binary search without off-by-one bugs, the bisect module, and insertion sort and merge sort written by hand.

   8 exercises

3. 3

   Stacks, Queues and Linked Lists

   Use a list as a stack and a deque as a queue, then build a linked list with O(1) append, search, removal and in-place reversal.

   8 exercises

4. 4

   Hash Maps and Two Pointers

   Turn O(n^2) searches into O(n) passes with dicts and sets, frequency counts, sliding windows and two pointers.

   8 exercises

5. 5

   Recursion, Trees and Graphs

   Think recursively, build a binary search tree, and explore graphs with depth-first and breadth-first search.

   8 exercises

6. 6

   Interview Problems

   Talk through a solution like a strong candidate, then solve five classic interview problems against edge cases and efficiency budgets.

   5 exercises

How you practice

You practice in the browser and every exercise gives you feedback right away. This course uses these formats:

• Code exercise: 24
• Predict the output: 5
• Multiple choice: 4
• Fix the bug: 4
• Match the pairs: 2
• Select all that apply: 2
• Spot the bug: 1
• Type the answer: 1
• Fill in the blank: 1
• Reorder lines: 1

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