Python for AI: A Crash Course

This will be an introduction to the Python programming language and Jupyter Notebooks, the “computational notebook” environment that you’ll use throughout this course. You’ll set up a Python programming environment, learn the basics of Jupyter Notebook and Python, and then apply those basics to build ELIZA, the original AI chatbot from the 1960s!

In the Python programming world, there is the concept of code being “Pythonic,” which means that it follows the conventions that the Python programming community has adopted. This lesson will cover advanced features of the Python programming language, as well as tried-and-true ways of writing Python that will make your code easier to understand and maintain — not just for yourself, but for everyone else.

One of the factors behind Python’s popularity is the large collection of libraries that its community has written over the decades. This lesson will explain what Python’s libraries are, how they work, and how to find libraries using PyPI, the Python package index. You’ll learn how to install Python libraries and create virtual environments to manage dependencies and ensure that your projects remain isolated from one another, avoiding conflicts between packages required by different projects.

AI applications are data-driven. This lesson will cover the first of two ways for your AI application to get data: from your local file system. It will focus on reading and writing data from your file system in two popular formats: CSV (comma-separated values) and JSON (JavaScript Object Notation).

Chances are that most of the data your AI applications will need aren’t in your local files, but available online through APIs (application programming interfaces). This lesson will cover what APIs are, how to communicate with them using HTTP methods and SDKs, and how your applications can use the information gathered from APIs.