Arrays, trees, graphs, sorting, and dynamic programming — explained from first principles with Python implementations. This course builds the intuition that makes algorithm problems feel like puzzles instead of mysteries.
This is a text-first course that links out to the best supporting material on the internet instead of trying to replace it. The goal is to make this the best course on data structures, algorithms, and computer science fundamentals you can find — even without producing a single minute of custom video.
This course is built by people who ship production data systems for a living. It reflects how things actually work on real projects — not how the documentation describes them.
Every day has working code snippets you can paste into your editor and run right now. The emphasis is on understanding what each line does, not memorizing syntax.
Instead of shooting videos that go stale in six months, Precision AI Academy links to the definitive open-source implementations, official documentation, and the best conference talks on the topic.
Each day is designed to finish in about an hour of focused reading plus hands-on work. You can do the whole course over a week of lunch breaks. No calendar commitment, no live classes, no quizzes.
Each day stands alone. Read them in order for the full picture, or jump straight to the day that answers the question you have today.
The three data structures you use every day. Memory layout, O(1) operations, collision resolution in hash maps, and when each structure is the right choice.
Binary trees, BSTs, AVL trees, and heaps. The recursive thinking pattern that makes tree problems tractable, and iterative alternatives for when the call stack matters.
Adjacency lists vs matrices, BFS, DFS, topological sort, Dijkstra, and Bellman-Ford. Every graph problem maps to one of these algorithms.
Merge sort, quick sort, heap sort, and binary search. When each sorting algorithm wins, and the interview questions that test your understanding of them.
Memoization, tabulation, and the two questions that reveal every DP structure: optimal substructure and overlapping subproblems. Fibonacci to knapsack to LCS.
Instead of shooting our own videos, Precision AI Academy links to the best deep-dives already on YouTube. Watch them alongside the course. All external, all free, all from builders who ship this stuff.
Comprehensive walkthroughs of every major data structure with Python code. From arrays to graphs.
The patterns behind DP problems: 1D DP, 2D DP, interval DP, and how to recognize which pattern applies.
BFS, DFS, Dijkstra, and topological sort animated and explained with code.
Time and space complexity analysis for every data structure and algorithm in this course.
The best way to understand any technology is to read the production-grade implementations that prove it works. These repositories implement patterns from every day of this course.
Python implementations of every algorithm in this course. The canonical open-source reference for algorithm study.
Clean, minimal Python implementations of data structures and algorithms. Good for reading after you understand a concept.
JavaScript implementations with Big O annotations for every algorithm. Useful companion to the Python examples.
The solutions to the NeetCode 150 — the most curated set of algorithm interview problems, organized by pattern.
Coding interviews test DSA. This course builds the pattern recognition that makes LeetCode problems feel systematic instead of random.
You build things but your CS fundamentals feel shaky. This course covers the structures and algorithms that every formal CS curriculum includes.
Your textbook is dry. This course covers the same material with Python code you can run and modify, and external videos that visualize the algorithms.
The 2-day in-person Precision AI Academy bootcamp covers data structures, algorithms, and computer science fundamentals hands-on. 5 U.S. cities. $1,490. 40 seats max. June–October 2026 (Thu–Fri).
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