Python

Why Python Dominates AI

When researchers and engineers build AI tools, they almost always reach for Python. There are two main reasons: its syntax is close to plain English (making it easy to learn and read), and its ecosystem of libraries is unmatched in the AI space.

Libraries like NumPy, pandas, PyTorch, and TensorFlow — the building blocks of modern AI — are all Python-first. When OpenAI, Anthropic, or Hugging Face release a new SDK, the Python version is always the most complete and best-documented.

The Ecosystem That Matters

A few Python libraries you'll encounter constantly in AI work:

• openai — the official Python SDK for OpenAI's API
• anthropic — the official SDK for Claude
• langchain — a framework for building LLM-powered apps
• numpy — fast numerical computing (used under the hood of almost everything)
• requests — making HTTP calls to APIs

Install any of these with pip install <name>.

Checking Your Installation

Run this in your terminal:

python --version

or on some systems:

python3 --version

You should see something like Python 3.11.4. If not, download Python from python.org and install it (tick the "Add to PATH" box on Windows).

Python vs JavaScript for AI

Both are valid choices. Python has more AI-specific libraries and is the default in research contexts. JavaScript/Node.js is better if you're building web-based AI apps. Many AI developers are comfortable in both.