Python for AI, Part 2: Conditionals and Functions

Python for AI, Part 2: Conditionals and Functions

1. Introduction
2. Conditionals in Python
3. Functions in Python
4. Why This Matters for AI
5. Try It Yourself: An Exercise
   1. Solution
6. Next Steps
7. Conclusion

Introduction

Welcome back to your journey of Python for AI! If you’ve got some Java and have gotten into the nitty-gritty of Python, with concepts such as variables and lists, you’re worthy of the next step: conditionals and And cut up the data as per the functions. These tools are essential for design decisions and organizing code — two fundamental skills for AI projects such as data processing or model building.

Conditionals in Python

Conditionals (if, elif, else) let your program decide what to do. They’re like Java’s if statements, but Python uses indentation instead of curly braces. Here’s an example classifying temperatures—an AI-like task:

temperature = 28

if temperature > 30:
    print("It’s hot!")
elif temperature > 20:
    print("It’s warm.")
else:
    print("It’s cool.")

Output: "It’s warm." Python checks conditions in order, stopping at the first true one. No parentheses or semicolons—simpler than Java, right?

Let’s combine it with a list and loop—think of this as analyzing a dataset:

temperatures = [25, 32, 18]
for temp in temperatures:
    if temp > 30:
        print(f"{temp}°C: Hot")
    elif temp > 20:
        print(f"{temp}°C: Warm")
    else:
        print(f"{temp}°C: Cool")

Output:

25°C: Warm
32°C: Hot
18°C: Cool

Functions in Python

Functions are like Java methods—reusable code blocks. In AI, they’re perfect for tasks like processing data. Here’s a simple one:

def greet(name):
    return f"Hello, {name}!"

print(greet("Alex"))  # Output: Hello, Alex!

Use def, no return type needed—unlike Java’s public String. Here’s a function for an AI scenario—checking thresholds:

def is_high(value, threshold):
    if value > threshold:
        return True
    else:
        return False

scores = [85, 92, 78, 95]
for score in scores:
    if is_high(score, 90):
        print(f"{score} is above 90!")

Output:

92 is above 90!
95 is above 90!

Why This Matters for AI

Conditionals help you filter data or make choices (e.g., "Is this value significant?"). Functions break down complex AI tasks into manageable pieces (e.g., calculating metrics). Together, they’re your toolkit for handling data—the heart of AI.

Try It Yourself: An Exercise

Write a program that:

1. Takes a list of numbers (e.g., [12, 15, 8, 20]).
2. Uses a function to check if each number is "big" (over 10).
3. Prints only the big numbers.

Here’s a starter:

numbers = [12, 15, 8, 20]

def is_big(num):
    # Add your if statement here
    pass  # Replace this

for num in numbers:
    # Call is_big and print if true

Hint: Use an if to check if num > 10, return True or False, then print based on that. Try it, then check below!

Solution

numbers = [12, 15, 8, 20]

def is_big(num):
    if num > 10:
        return True
    else:
        return False

for num in numbers:
    if is_big(num):
        print(f"{num} is big!")

Output:

12 is big!
15 is big!
20 is big!

Next Steps

You’re working with conditionals and functions—fabulous! Next, we’ll look into Python libraries such as NumPy for working with bigger datasets that brings you one step closer to AI. Practice this exercise, adjust it (for example, modify the threshold), and tell me how it turns out!

Conclusion

With conditionals and functions, you’re developing skills that AI is based on. In the meantime, keep playing around, and soon you’ll be ready for the real AI tools. Happy coding!