Intermediate10-12 hours

Data Structures & Algorithms: Foundations

Build genuine fluency in the data structures and algorithm patterns that underpin everyday engineering. Python-first, pattern-by-pattern, grounded in the kind of problems a working AI engineer actually reasons about — and why each tool exists.

What You'll Learn

PythonAlgorithmsData StructuresProblem Solving

Learning Outcomes

✓Reach for the right Python tool — Counter, deque, heapq, bisect — and know when each is the wrong choice
✓Reason about time and space complexity, and explain the trade-offs out loud
✓Recognize the dominant patterns: hashing, two pointers, sliding window, binary search
✓Traverse and manipulate trees, linked lists, and graphs with confidence
✓Decompose an unfamiliar problem into a known pattern before writing code

Course Modules

1theory60 minutes

Python Essentials & Big-O

The standard-library toolkit and a working mental model of complexity classes — what each tool does, and when it is the wrong one

2hands-on75 minutes

Arrays, Strings & Hashing

Frequency maps, deduplication, and prefix sums — the patterns behind a huge share of everyday array and string problems

3hands-on75 minutes

Two Pointers & Sliding Window

Linear-time techniques for substrings, pair sums, and in-place partitioning

4hands-on60 minutes

Stacks & Queues

Valid-parentheses, monotonic stacks, and BFS scaffolding with deque

5hands-on60 minutes

Binary Search

Search sorted arrays and — the trick most miss — search the answer space itself

6hands-on60 minutes

Linked Lists

Reverse, detect cycles with Floyd, and merge — pointer manipulation without the panic

7hands-on90 minutes

Trees & Binary Search Trees

Recursive and iterative traversals, depth, LCA, validate-BST, and level order

8hands-on90 minutes

Graphs

BFS/DFS, connected components, topological sort, and Union-Find — the same intuition behind real workflow cycle detection

Ready to Start Learning?

Join engineers mastering production agentic AI — from architecture to deployment.