Who Am I?

• Mr. Peticolas ("Mr. P").
• I've worked at startups on Data Science teams for 11 years.
• I'm currently at Oden Technologies where I build and deploy Data Science and Machine Learning for plastics manufacturing.
• This is my first time teaching at Columbia.

Python

A general-purpose programming language popular in Data Science.

Data Science

The process of extracting knowledge from data.

Machine Learning

A subset of Data Science that uses algorithms to learn from data.

Machine Learning

is an application of Data Science.

Python

is a programming language.

Data Science

is most often done in Python.

There are three kinds of lies: lies, damned lies, and statistics.
~ Benjamin Disraeli, polularized by Mark Twain

Machine Learning is Sneaking Into Day-to-Day Life

Fields That Use Data Science

Course Objectives

1. Produce basic Python programs capable of user input/output.
2. Use data from CSVs, relational databases, and the web in code.
3. Employ Data Science packages to perform adhoc data analysis.
4. Calculate, plot, and present analsysis from data with Python.
5. Model problems with Supervised and Unsupervised ML.
6. Identify the use of neural nets in modern AI.

Week 1: Python

• Introduction to Python and programming (no prior experience)
• Variables, data types, and control flow
• Functions, data structures, and file I/O
• Classes and objects
• Libraries and modules
• Pandas and working with tabular data

Week 2: Data Science

• What is Data?
• Data Formats
• Data Visualization
• Time Series Data
• Natural Language Processing

Week 3: Machine Learning

• Introduction to Machine Learning
• Supervised and Unsupervised Learning
• Neural Networks
• Deep Learning
• How these tools forms the basis of modern AI

Assignments

• Basic Python Exercises in Google Colab Notebooks
• Building a Text Adventure Game
• CSV Data Analysis
• Natural Language Processing with Music Lyrics
• Time Series Data Analysis
• Image Classification with Pytorch

• We will use computers with keyboards.
• All python will be written in Jupyter Notebooks.
• We will use Google Colab for running Jupyter notebooks.
  • Online platform for running Jupyter notebooks.
  • Free access to computing resources.
  • Integrates with Google Drive and Github.
• We will share data on Google Drive

About Using ChatGPT, Gemini, etc.

I encourage you to use all of the tools at your disposal to learn.

However, for many portions of this class, you will be hindering yourself by using these. For the first few lectures, turn them off and figure it out on your own.

You will learn more and be better prepared to use (and debug) them in the future.

I will tell you when it's time to turn them on.

Your First Exercise

1. Set up Google Colab and create a new notebook.
2. Write a program that prints "Hello, World!"print("Hello, World!")
3. Do some mathprint("What is 3 + 4?", 3 + 2) print("What is 6 - 7?", 6 - 7) print("Is it true that 3 + 4 < 6 - 7?", 3 + 4 < 6 - 7)