Add multilingual language and systems learning tracks

en/expanded-26-1/README.md

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+# Algorithms & Data Structures · 1
+
+[Agila University track](https://edu.agilaos.com/track.php?track=26&lang=en)
+
+About 15 minutes per lesson. Predict, run, change, explain, then complete the check in University.
+
+- [Lesson 1: Count the work in a search](lesson-1/lesson.html)
+- [Lesson 2: Use a queue when order matters](lesson-2/lesson.html)
+- [Lesson 3: Binary search needs an invariant](lesson-3/lesson.html)

en/expanded-26-1/lesson-1/lesson.html

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+<!doctype html><html lang="en"><meta charset="utf-8"><title>Count the work in a search</title><h1>Count the work in a search</h1><p>15-minute session: read for 3 minutes, trace for 3, experiment for 7, and complete the check for 2. Spend longer whenever you need.</p><p>Linear search may inspect every element. Count comparisons for a match at the start, a match at the end, and a missing value. Big-O describes growth, not a measured duration on your machine. Compare sizes 10, 100, and 1000 before choosing a different structure.</p><p><strong>Practice and evidence:</strong> Predict the example or draw its state transitions. Change one assumption, test the boundary, and record the actual result. Explain what this small model does not establish about a production system.</p><pre><code class="language-python">items=list(range(10))
+checks=0
+for value in items:
+    checks+=1
+    if value==9:break
+print(checks)
+</code></pre><p><strong>Expected result:</strong> <code>10</code></p><h3>Practice and evidence</h3><p>Keep three notes: your prediction, the actual result, and why they match or differ. The completion check grades understanding; the practice task builds skill.</p></html>

en/expanded-26-1/lesson-1/main.py

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+items=list(range(10))
+checks=0
+for value in items:
+    checks+=1
+    if value==9:break
+print(checks)

en/expanded-26-1/lesson-2/lesson.html

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+<!doctype html><html lang="en"><meta charset="utf-8"><title>Use a queue when order matters</title><h1>Use a queue when order matters</h1><p>15-minute session: read for 3 minutes, trace for 3, experiment for 7, and complete the check for 2. Spend longer whenever you need.</p><p>FIFO removes the oldest item first. Use a deque for a work queue instead of repeatedly removing index zero from a long list. Specify capacity and what happens when it fills. Test empty, one-item, and full states; an efficient structure still needs a correct policy.</p><p><strong>Practice and evidence:</strong> Predict the example or draw its state transitions. Change one assumption, test the boundary, and record the actual result. Explain what this small model does not establish about a production system.</p><pre><code class="language-python">from collections import deque
+queue=deque([&quot;A&quot;,&quot;B&quot;])
+print(queue.popleft())
+queue.append(&quot;C&quot;)
+print(list(queue))
+</code></pre><p><strong>Expected result:</strong> <code>A
+[&#x27;B&#x27;, &#x27;C&#x27;]</code></p><h3>Practice and evidence</h3><p>Keep three notes: your prediction, the actual result, and why they match or differ. The completion check grades understanding; the practice task builds skill.</p></html>

en/expanded-26-1/lesson-2/main.py

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+from collections import deque
+queue=deque(["A","B"])
+print(queue.popleft())
+queue.append("C")
+print(list(queue))

en/expanded-26-1/lesson-3/lesson.html

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+<!doctype html><html lang="en"><meta charset="utf-8"><title>Binary search needs an invariant</title><h1>Binary search needs an invariant</h1><p>15-minute session: read for 3 minutes, trace for 3, experiment for 7, and complete the check for 2. Spend longer whenever you need.</p><p>Binary search relies on sorted data and a shrinking search interval. A faster loop on unsorted data can return a wrong answer. Use a library operation, test insertion at both ends and an existing value, then explain the invariant before implementing your own.</p><p><strong>Practice and evidence:</strong> Predict the example or draw its state transitions. Change one assumption, test the boundary, and record the actual result. Explain what this small model does not establish about a production system.</p><pre><code class="language-python">from bisect import bisect_left
+values=[2,4,6]
+print(bisect_left(values,1))
+print(bisect_left(values,4))
+print(bisect_left(values,8))
+</code></pre><p><strong>Expected result:</strong> <code>0
+1
+3</code></p><h3>Practice and evidence</h3><p>Keep three notes: your prediction, the actual result, and why they match or differ. The completion check grades understanding; the practice task builds skill.</p></html>

en/expanded-26-1/lesson-3/main.py

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+from bisect import bisect_left
+values=[2,4,6]
+print(bisect_left(values,1))
+print(bisect_left(values,4))
+print(bisect_left(values,8))