Python for AI Intro

Why Python?

If you look at job descriptions for AI, you'll see one word over and over: Python.

But why? Is it the fastest language? (No.) Is it the newest? (No, it's from 1991!)

Python is the king of AI for two reasons:

It's Readable: Python code looks a lot like plain English. It's easy to learn and easy to read.
The Ecosystem: Over the years, thousands of people have built free "add-ons" (libraries) for Python that do the hard math of AI for you.

Reading Your First Code

Let's look at how simple Python is. Here is how you print a message to the screen:

print("Hello, AI!")

That's it. No curly braces {}, no semicolons ;. Just the command.

Variables: Storing Info

Think of a variable like a box with a label. You can put things in it.


# Create a box named 'robot_name' and put "R2-D2" inside
robot_name = "R2-D2"

# Create a box named 'battery_level' and put 85 inside
battery_level = 85

print(robot_name)

# Output: R2-D2

The Power of Libraries

You don't build a house by making your own bricks and cutting your own trees. You buy materials.
In Python, Libraries are your pre-made materials.

Pandas: Like Excel for code. Great for organizing data.
OpenAI: A library that lets you talk to ChatGPT from your code.

Example: Talking to AI

Here is what "real" AI code looks like (simplified):

import openai

# Bring in the AI tool

# Send a message
response = openai.ChatCompletion.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Tell me a joke"}]
)

# Print the answer
print(response)

You don't need to know how the AI works inside. You just need to know how to use the library to send the message.

Conclusion

Learning Python is the first step to building your own AI apps. You don't need to be a math genius. You just need to learn the basic grammar of the language and how to use the amazing tools others have built.