AI Ninja Program

Security Engineers AI-Powered Security Experts

Classic ML

Foundations of machine learning with scikit-learn

AI Foundations · ~7.7 hrs
1
What is Machine Learning?
Explore the digits dataset interactively
2
Linear Regression
Predict continuous values with a straight line
3
Logistic Regression
Binary classification and decision boundaries
4
Decision Trees
Tree-based models and feature importance
5
Model Evaluation
Metrics, cross-validation, and overfitting

Intermediate ML

Feature engineering, ensembles, and unsupervised learning

AI Foundations · ~6.0 hrs
1
Feature Engineering
Transform raw data into useful features
2
Random Forests
Ensemble methods and bagging
3
k-Means Clustering
Unsupervised learning for security
4
Cross-Validation & Overfitting
Generalization and model selection

Generative AI

LLMs, APIs, RAG, and prompt engineering

AI Ninja · ~6.5 hrs
1
How LLMs Work
Transformers, tokens, and attention
2
HuggingFace Pre-trained Models
Open-source model hub and inference
3
Working with LLM APIs
Building applications with LLM APIs
4
Retrieval-Augmented Generation
Retrieve, augment, generate — ground LLMs in your docs

Neural Networks

Deep learning from perceptrons to CNNs

AI Practitioner · ~7.0 hrs
1
First Neural Network in Keras
Build a neural network from scratch
2
Deeper Networks & Dropout
Prevent overfitting in deep networks
3
Convolutional Neural Networks
Image recognition with CNNs
4
Hyperparameters & Tuning
Systematic model optimization

CP AI Security

Check Point AI product positioning and demos

AI Ninja · ~4.0 hrs
1
Workforce AI Security
Securing workforce AI usage
2
AI Agent Security + MCP
Protecting autonomous AI agents
3
AI Guardrails
Content safety and policy enforcement
4
Positioning Check Point AI Security
Technical depth for customer engagements