Mathematical Foundations of Data Science

Course Materials and Notes

1. Introduction

Fundamentals and basic concepts of data science.

2. Supervised Learning

Methods and algorithms for prediction and classification with labeled data.

3. Unsupervised Learning

Techniques for finding patterns in unlabeled data.

About These Materials

These course materials are derived from the official course curriculum with supplementary notes and explanations added to enhance comprehension and clarity.
While every effort has been made to ensure accuracy, these notes represent personal interpretations of the course content.

Please note that these materials are provided for educational purposes only.
I don't give any warranties regarding completeness, reliability, or accuracy of the content and disclaim responsibility for any errors, omissions, or misinterpretations that may be present.

For authoritative information, students should always refer to the official course materials and consult with course instructors.