Targeting practitioners in data science and analytics, this book introduces key concepts in data analytics through practical applications using Python tools like SciKit Learn, Pandas, and Numpy. It serves as a resource for both academic and business contexts, emphasizing hands-on learning to enhance understanding of data analysis techniques.
Focusing on practical application, this text equips students in physics, engineering, and related fields with essential commands and structures for MATLAB® and Octave. By emphasizing the similarities in syntax, it enables learners to write code applicable in both environments. Designed for accessibility, it assumes no prior programming knowledge, making it suitable for a diverse student audience. The book simplifies complex concepts, allowing students to harness the full potential of these programming languages effectively.
The book is intended for practitioners in data science and data analytics in both academic and business environments. It aims to present the reader with concepts in data science and analytics that were deemed to be more advanced or simply out of scope in the author's first book.