For a few years, I have been teaching an introductory random processes course. I have found, that “Intuitive Probability and Random Processes using MATLAB®” by Steven Kay, published in 2006, is an exceptional resource. While Kay’s “Fundamentals of Statistical Signal Processing” consists of three volumes packed with advanced mathematical theory, his more recent work combines practical engineering approaches with simulations that are appropriate for undergraduate students.

Nevertheless, I recently came across a remarkable new book that I am going to adopt. This book, titled “Introduction to Probability for Data Science” by Stanley H. Chan, available for free through the “Free ECE Textbook Initiative.” I was pleasantly surprised by its modern design and the inclusion of both theory and code. It also aligns with an ECE background and supports both Matlab and Python. The supplementary homepage is also highly recommended. It’s also important to note the introductory material related to machine learning and data science, as it can be beneficial for follow-up courses.

I suggest that for the next edition of this book, the author could enhance the Exercise sections by his including previous homework and exams as questions.

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