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Welcome to the Lab 🛠️

Understanding algorithms is crucial for programming. AI can act as your personal tutor, explaining concepts, step-by-step logic, and example code. In this lesson, you’ll learn how to prompt AI to teach algorithms effectively, so you can understand, implement, and optimize them.

Step 0: Define Your Goal

Scenario: You want to learn how the Bubble Sort algorithm works and see a Python implementation.

• Input: A list of numbers
• Output: Sorted list + explanation of each step

Mini-challenge: Write down in plain English what you want to understand about Bubble Sort.

Step 1: Crafting Your Prompt

Good prompts for algorithm explanation include:

1. The algorithm name or problem
2. Request for step-by-step explanation
3. Optional: Python code implementation, complexity analysis

Example Prompt (Step-by-Step Explanation + Code):

Explain how the Bubble Sort algorithm works step by step. 
Provide a Python implementation and explain each line of code.

Step 2: AI Output Example

Explanation:

1. Compare each adjacent pair in the list.
2. Swap if the first element is greater than the second.
3. Repeat until no swaps are needed (list is sorted).

Python Code:

def bubble_sort(arr):
    n = len(arr)
    for i in range(n):
        swapped = False
        for j in range(0, n-i-1):
            if arr[j] > arr[j+1]:
                arr[j], arr[j+1] = arr[j+1], arr[j]
                swapped = True
        if not swapped:
            break
    return arr

Step-by-Step Explanation of Code:

• n = len(arr) → get the length of the list
• Outer loop for i in range(n) → iterate through each pass
• swapped = False → track if any swap happens
• Inner loop for j in range(0, n-i-1) → compare adjacent elements
• Swap if arr[j] > arr[j+1]
• If no swaps in a pass, break → optimization

Step 3: Test the Algorithm

numbers = [5, 2, 9, 1, 5, 6]
print(bubble_sort(numbers))  # Output: [1, 2, 5, 5, 6, 9]

Step 4: Mini Lab Challenges

1. Ask AI to explain and implement Merge Sort step by step.
2. Generate a visual explanation using comments in the code for each comparison and swap.
3. Compare Bubble Sort vs Selection Sort explanations.
4. Ask AI to provide time and space complexity analysis for any algorithm.

Step 5: Pro Tips

• Use explicit instructions: step-by-step explanation, line-by-line code, complexity analysis.
• Ask AI for examples with different data types (integers, strings, etc.).
• For teaching purposes, request comments and reasoning inside the code.
• Iteratively refine prompts for clarity and depth.

Lab Summary

• AI can serve as a personal algorithm tutor, explaining logic, steps, and code.
• Clear, step-focused prompts yield better explanations.
• Combining explanations with code accelerates understanding.
• Iteration is key: refine prompts, test examples, and explore variations.