Paths, Not Courses
This isn’t a course — it’s a playground for learning by doing to master programming concepts and best practices.
PixelProcess is designed for exploration with working, interactive code examples. Content is organized for progressive learning, but modular code snippets and notebooks allow for quick testing and reference.
PxP is designed to get fingers on keyboards-from learning the basics of Python to full ML workflows. The design is aimed at removing friction, getting started fast, and understanding core concepts. Code has bugs built in often to address real-world issues that come up and tips for resolving them.
-New to programming? Try Python
-Wrangling data? Explore Data
-Deriving insight from data? Build Models
-Updating tools and workflow? Create Code
-Ready to run notebooks? Binder Quickstart
Try Python
Code Freely | Fail Safely | Start Quickly
Interactive quick start content to get new users reading, editing, and running code in seconds. Explore basic programming concepts in Python including datatypes, operators, variables, and more.
Explore Data
Summarize Data | Develop Habits | Grow Confident
Explore data analysis fundamentals for working with and summarizing datasets. Learn about key packages and code for data input/output (I/O), cleaning, summarizing, analyzing, and visualizing data.
Build Models
Clean Data | Fit Models | Test Performance
Understand how machines learn with deep-dive, code based algorithm examples and complete analysis workflows that cover data I/O, splits, training, testing, and evaluation.
Check out Data Science Topics for common ML usage, metrics, and terminology.
Create Code
Save Time | Avoid Errors | Create Flow
Work efficiently with the right environment, tools, and mindset to code like a pro. From command line aliases, to project standards, to pro-tips for debugging, this section is designed to make your life easier.
From experience, I can attest learning everything is overwhelming, exhausting, and unnecessary. Focus on what you want to build or understand. Learn what you need as you go. And don’t be afraid to change course — that’s part of the process, too.
Start small — expertise doesn’t happen in a day
Iterate often — progress comes through refactoring, revisiting, and rethinking
Improve always — focus on what matters now, and let your skills grow with your goals
Code is read more often than it is written
Programming is more about problem-solving than memorization. Looking up syntax, reading the docs, and debugging are required, but getting-started and working on real projects is essential. Experience and expertise grow with time and effort.