EC101: Programming as Thinking

Python, Logic, and Human Reasoning

Variables as memory, functions as abstraction, code as formalized thought

📋 Overview

You've learned how humans think. Now learn how to formalize that thinking into code.

Programming isn't about memorizing syntax—it's about taking the cognitive patterns you already use and expressing them in a language computers understand.

What You'll Learn:

• Variables as named thoughts in working memory
• Functions as chunking mechanisms
• Branching as decision modeling
• Loops as cycles of refinement
• Data modeling as meaning modeling

🎯 Key Outcomes

By the end of this course, you will:

• Write Python code that solves real problems
• Understand why code is structured the way it is (not just how)
• Think algorithmically about everyday tasks
• Debug systematically using metacognitive loops
• Model problems before writing code

📚 Prerequisites

• EC000 - Understanding cognition as a system

🗺️ Course Structure

Module 1: Variables & Memory

Focus: Storing and manipulating information

Lessons:

• 1.1 - Variables as Named Thoughts: Why we name things
• 1.2 - Types as Categories: How computers classify information
• 1.3 - Scope & Context: When variables exist and die

Project: Build a personal information tracker

Module 2: Functions & Abstraction

Focus: Chunking procedures

Lessons:

• 2.1 - Functions as Mental Chunks: Packaging thought patterns
• 2.2 - Parameters & Arguments: Inputs to procedures
• 2.3 - Return Values: Outputs from computation

Project: Create a library of reusable utility functions

Module 3: Control Flow

Focus: Modeling decisions and repetition

Lessons:

• 3.1 - Conditionals as Decisions: If/else as choice points
• 3.2 - Loops as Refinement: Iteration in thought and code
• 3.3 - Breaking & Continuing: Escaping loops intelligently

Project: Build a text-based decision tree game

Module 4: Data Structures Intro

Focus: Organizing information

Lessons:

• 4.1 - Lists as Sequences: Ordered collections
• 4.2 - Dictionaries as Associations: Key-value thinking
• 4.3 - Choosing the Right Structure: When to use what

Project: Create a contact management system

Module 5: Problem Decomposition

Focus: Breaking problems into solvable pieces

Lessons:

• 5.1 - Top-Down Thinking: Starting with the big picture
• 5.2 - Bottom-Up Building: Assembling from components
• 5.3 - Debugging as Hypothesis Testing: Scientific problem-solving

Project: Build a complete application from scratch

🔗 Connections

Builds On

• EC000 - All cognitive concepts from EC000 appear here in code

Leads To

• EC102 - Deep dive into organizing information
• EC103 - Understanding state and memory systems

Used In Hackathon Lab

• Every hackathon week uses these foundational concepts

💡 Key Concepts

Concept 1: Variables = Named Thoughts

Just like you hold thoughts in working memory, variables hold values in computer memory. Naming them well makes code readable.

In Practice: user_age is better than x

Concept 2: Functions = Chunking

Experts don't think in individual steps—they think in chunks. Functions let you do the same in code.

In Practice: calculate_discount(price, percentage) chunks pricing logic

Concept 3: Loops = Mental Cycles

You naturally iterate ("try again until it works"). Loops formalize this.

In Practice: while not solved: try_solution()

🛠️ Practical Applications

1. Automate repetitive tasks in your daily life
2. Think more clearly about problem-solving
3. Build tools that serve real needs
4. Prototype ideas quickly

📖 Resources

• Reading: "Think Python" by Allen Downey
• Practice: Daily coding challenges
• Community: community

🚀 Getting Started

Difficulty: ⭐⭐☆☆☆ Beginner
Time Commitment: ~12 hours
Prerequisites: EC000
Next Course: EC102