Those just starting out in the field of data science sometimes find themselves among a plethora of “data science hype” that leaves them feeling confused and overwhelmed. Many common phrases and concepts, such as “big data,” “artificial intelligence,” and “data science,” lack clear definitions. The size of large data. Define data science. When compared to the more common “Data Analyst,” what distinguishes the “Data Scientist?” Numerous ideas are conjured up when one hears the word “data science,” including machine learning (ML), deep learning along with data mining, and pattern recognition. As professional data scientists, we found all of them to be imprecise and unclear. Yet, the applications of data science are constantly providing us with something real, and they have been progressing rapidly. Years of experience with data science applications have led to a far deeper understanding of the field as a whole. With this book, aspires to give data science greater credibility and solid grounding. The book goes beyond the “hard” technical components of data science to discuss topics like soft skills and the evolution of the field as a career path.