Public Accountability Operations: Public-Interest Undercover Investigation

Course overview

Learn ethical public-interest field methods, open-methods exhaustion, field observation, recording discipline, and visual evidence integrity for accountability operations.

Course Module

Start Here

What is AI?
Types of AI (Narrow, General, Super intelligent)
Real-world AI use cases
Machine learning vs. traditional programming

Lesson 1 — Ethical Field Approach & Open-Methods Exhaustion

What is data? (structured vs unstructured)
Types of data (numerical, categorical, text, images)
Data collection methods
Data cleaning & preprocessing basics
Training data vs testing data

Lesson 2 — Field Recording, Observation & Visual Evidence Integrity

What is supervised learning?
Regression vs classification
Common algorithms (Linear Regression, Logistic Regression, KNN, Decision Trees)
Feature selection & labels
Real-world supervised learning examples

Guided Case Lab™ — Open Discussion & Feedback

What is unsupervised learning?
Clustering concepts (K-Means, Hierarchical clustering)
Dimensionality reduction (PCA basics)
Pattern discovery & grouping data
Real-world use cases (customer segmentation, recommendation)

Final Project — Public-Interest Undercover Investigation Portfolio

Introduction to neural networks
How neurons, layers & activation functions work
Feedforward vs backpropagation
Deep learning vs traditional ML
Real-world applications (image recognition, NLP)

Meet Your Instructors

Larry Margulies

Founder, Lead Instructor & Case Advocate

Founder of DIY Detective™ and creator of the Drawn Evidence™ visual-intelligence training system. Larry leads instruction in visual investigation, case architecture, public accountability, and civilian case advocacy. Selected courses may also feature guest experts and specialist instructors with professional experience in relevant fields.

What Students Say.

Student experiences and feedback will appear here as the Drawn Evidence™ community grows.

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Course Participant

Drawn Evidence™ Community

Student experiences and feedback will appear here as the Drawn Evidence™ community grows.

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Course Participant

Drawn Evidence™ Community

Student experiences and feedback will appear here as the Drawn Evidence™ community grows.

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Course Participant

Drawn Evidence™ Community

This course completely changed how I understand AI. The instructor broke down even the most complex topics—like neural networks and gradient descent—into simple, digestible lessons. The hands-on exercises helped me finally connect theory with practical implementation.