الخوارزميات وهياكل البيانات
Big O والبحث والفرز والهياكل التي تقوم عليها.
Algorithms are the recipes behind every fast app, and data structures are the containers those recipes work on. This track teaches the ideas every developer is expected to know: counting steps with Big O, searching with linear and binary search, and choosing between lists, hash maps, sets, stacks and queues. Then you will write recursion with memoization, see how merge sort reaches n log n, and walk a friends network with breadth-first search. The last module goes further with search trees, heaps, dynamic programming and Dijkstra's shortest paths.
Every example is short, runnable Python that works on everyday app data: scores, usernames, leaderboards and friends. Basic Python (variables, loops, functions, lists and dicts) is all you need to start.
- الدروس
- ١٤
- الوقت
- ٢ ساعة
- المستوى
- مبتدئ
دروس هذا المسار بالإنجليزية حاليًا.
- البرونز متاحة
- الفضة متاحة
- الذهب مقفلة
مستعد لإثبات نفسك؟
ثلاثة امتحانات في انتظارك: البرونز والفضة والذهب.
ما ستتمكن من فعله
- Count an algorithm's steps and describe its growth with Big O
- Search with linear and binary search, without off-by-one bugs
- Pick the right structure: list, dict, set, stack or queue
- Write recursive functions and speed them up with memoization and dynamic programming
- Explain why merge sort is O(n log n), and sort real data with
sorted() - Walk a network with breadth-first search and find the cheapest route with Dijkstra's algorithm
الرحلة
١ الوحدة ١Thinking in steps
What an algorithm is, what Big O says, and searching a list one item at a time or by halves.
٠ / ٤٢ الوحدة ٢Structures that make code fast
Hash maps and sets, stacks and queues, recursion, sorting and graphs.
٠ / ٦٣ الوحدة ٣Going further
Search trees, heaps, dynamic programming and shortest paths.
٠ / ٤