Machine Learning for N00bs


Machine Learning CTF

Awareness: Demonstrating Capabilities

ML 100: Machine Learning with TensorFlow (65 pts extra)
ML 101: Computer Vision (10 pts extra)
ML 102: Breaking a CAPTCHA (10 pts extra)
ML 103: Deblurring Images (40 pts extra)

Technical: Inner Components

ML 104: Analyzing Input Data (20 pts extra)
ML 105: Classification (15 pts extra)
ML 106: Data Poisoning (10 pts extra)


ML 107: Evasion Attack with SecML (40 pts extra)
ML 108: Evasion Attack on MNIST dataset (40 pts extra)
ML 109: Poisoning Labels with SecML (30 pts extra)
ML 110: Poisoning by Gradients (40 pts extra)
ML 111: Poisoning the MNIST datase (40 pts extra)

Large Language Models

ML 120: Bloom LLM (30 pts extra)
ML 121: Prompt Engineering Concepts (20 pts extra)
ML 122: Comparing LLMs on Colab (20 pts extra)
ML 130: Prompt Injection (95 pts extra)

Under Development

  • The Cleverhans attack library
  • Deep Neural Rejection (a defense mechanism)
  • Detecting Malware
  • Linear and polynomial regression
  • Overfitting and underfitting


SecML: Secure and Explainable Machine Learning in Python
ChatGPT Prompt Engineering for Developers
Prompt Engineering Guide
Google's Generative AI learning path

Archived Scores

Spring 2023

Posted: 6-8-23