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Understanding Prompts
ML 130:
Prompt Injection (25 pts + 60 extra)
ML 131:
Generating Python Code with Bard (40 pts extra)
Violent Python Challenges (extra)
Google Learning
GL_Badges:
Google Learning (30 pts + 60 or more extra)
Awareness: Demonstrating Capabilities
ML 100:
Machine Learning with TensorFlow (20 pts + 45 extra)
ML 101:
Computer Vision (10 pts)
ML 102:
Breaking a CAPTCHA (10 pts)
ML 103:
Deblurring Images (10 pts + 30 extra)
Technical: Inner Components
ML 104:
Analyzing Input Data (20 pts)
ML 105:
Classification (15 pts + 10 extra)
ML 106:
Data Poisoning (10 pts)
ML 112:
Support Vector Machines (40 pts extra)
ML 113:
Decision Trees (15 pts extra)
ML 114:
Ensemble Learning and Random Forests (15 pts extra)
ML 115:
Dimensionality Reduction (20 pts extra)
ML 116:
k-Means Clustering (30 pts extra)
Attacks
ML 107:
Evasion Attack with SecML (15 pts + 25 extra)
ML 108:
Evasion Attack on MNIST dataset (20 pts + 20 extra)
ML 109:
Poisoning Labels with SecML (20 pts + 10 extra)
ML 110:
Poisoning by Gradients (15 pts + 15 extra)
ML 111:
Poisoning the MNIST dataset (20 pts + 20 extra)
Defenses
ML 140:
Deep Neural Rejection (45 pts extra)
Large Language Models
ML 120:
Bloom LLM (15 pts + 15 extra)
ML 121:
Prompt Engineering Concepts (20 pts)
ML 122:
Comparing LLMs on Colab (10 pts + 10 extra)
Code Scanning
W 700: SonarQube Code Scanner (15 pts)
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