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Applied statistics and Probability for Computer Scientists

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Applied statistics and Probability for Computer Scientists

About The course

This course provides a comprehensive introduction to applied statistics and probability theory, tailored specifically for computer scientists. It covers fundamental concepts and techniques that are essential for data analysis, machine learning, and algorithm design.

Prerequisites

Basic knowledge of:

  • Python programming

  • Linear algebra

  • Calculus (introductory level)

References

Forsyth, D. (2018). Probability and Statistics for Computer Science. Springer International Publishing.

Part I - Describing Datasets
Chapter 1: First Tools for Looking at Data