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Programming · course 18 of 105

Python Coding Interviews, Pattern by Pattern

Solve beginner and mid-level coding interview problems in Python: Big-O, hash maps, two pointers, sliding windows, binary search and recursion, graded on hidden tests.

3 modules

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Runs in Claude (claude.ai, the Claude apps or Claude Code) with your own Claude account. A course opens there as soon as your payment goes through; nothing is shipped.

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What it teaches

The patterns behind many beginner and mid-level coding interview questions, in Python: Big-O and what Python’s lists, sets and dicts really cost; hash maps for counting, grouping and two sum; two pointers; fixed and variable sliding windows; prefix sums; stacks for brackets; queues with deque; binary search (and bisect); merging intervals; recursion. The AI asks 3 questions, places you, shows a short rule card per module, then gives you one problem at a time: trace what a pattern prints, or write the function, graded on hidden tests (empty input, ties, one item).

Job seekers and students preparing for a first developer job or internship who know Python basics but freeze on interview problems.

How long

42 items in the banks. A beginner needs about 50-70 rounds (68 in the AI-simulated test run), a strong student about 15-30, plus a 12-item final: 2-4 sessions (estimate, not timed with a real student). The tutor gives a one-line save code at the end of each session.

The modules

3 modules, drilled one item at a time.

  1. M1

    Big-O, hash maps and sets

    Say what the code prints or which error stops it, write the function, or answer a concept question

  2. M2

    Two pointers, sliding windows and prefix sums

    Say what the code prints or which error stops it, write the function, or answer a concept question

  3. M3

    Stacks, queues, binary search, intervals and recursion

    Say what the code prints or which error stops it, write the function, or answer a concept question

Before it teaches, it asks

  1. 1
    What are you preparing for (a first developer job, a move to a bigger company, an internship)? Have you done practice problems before (LeetCode or similar)? Can you run Python on your computer right now (fine to say no)?
  2. 2
    What does this print? If it stops with an error, name the error.def two_sum(nums, target):seen = {}for i, n in enumerate(nums):if target - n in seen:return [seen[target - n], i]seen[n] = ireturn None print(two_sum([2, 7, 11, 15], 9))
  3. 3
    What does this print? If it stops with an error, name the error.
    Show the code it asks about (10 lines)def longest_unique(s):seen = {}start = best = 0for i, ch in enumerate(s):if ch in seen and seen[ch] >= start:start = seen[ch] + 1seen[ch] = ibest = max(best, i - start + 1)return best print(longest_unique("abcabcbb"), longest_unique("bbbb"))

What’s exact, and what isn’t

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Straight from the course’s own notes.

Exact
Every key, Test result and trap result was produced by running the code on Python 3.14.3 and again on 3.9.6, with no difference. 33 items (19 trace, 14 write the function) plus 9 concept questions. Every accepted answer passes every test. A planted-error test (3 errors) was caught.
Sourced
Big-O costs from the Python wiki’s TimeComplexity page and the Library Reference (short quotes, matched on the pages on 2026-10-10).
Judgment
When your code isn’t one the key lists, the AI traces it on every test and shows a Check: line. Speed is judged only through the tests; a slower answer that passes is right, and the tutor names its Big-O.
Not in it yet
Dynamic programming, graphs, trees, heaps, linked lists.