Introduction to Machine Learning

Fall 2025 • American University of Beirut

Course Schedule

Introduction to Machine Learning • Fall 2025

Introduction

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Aug 26
1
Introduction, Ethics/Purpose of AI, Logistics
Course foundations and logistics
75 min Lecture
Course introduction covering learning objectives, expectations, and motivation. Exploration of AI's transformative impact on society and discussion of ethical implications in AI development and deployment.
Lecture
Articles
Aug 28
2
Data, Models, and Python
75 min Lecture
Lecture
References
  • Data Visualization Example (coming soon) Recommended
Sep 2
3
Math and Python Review - Your Computational Toolkit
Linear algebra meets computational implementation
75 min Lecture
Comprehensive review of mathematical foundations essential for machine learning, combined with hands-on Python implementation. Students will bridge the gap between mathematical notation and computational implementation through interactive notebooks that combine CS229 linear algebra concepts with NumPy code examples.
Preparation
Lecture
References

Function Approximation

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Sep 4
4
Supervised Learning and Linear Regression
First machine learning algorithm and foundational concepts
75 min Lecture
Introduction to supervised learning paradigm with linear regression as the first ML algorithm. Mathematical foundations, implementation, and practical applications with hands-on coding.
Lecture
Sep 9
5
Feature Engineering and Generalization
From raw data to meaningful features, avoiding overfitting
75 min Lecture
Deep dive into feature engineering techniques and understanding generalization. Covers bias-variance tradeoff, cross-validation, and regularization methods.
Lecture
Sep 11
6
Classification and Logistic Regression
From regression to classification with probabilistic models
75 min Lecture
Introduction to classification problems using logistic regression. Covers sigmoid function, maximum likelihood estimation, and decision boundaries.
Lecture

This schedule is dynamically generated from lecture metadata. Materials and links are updated as they become available.