The role of Data Scientist was dubbed "The sexiest job of the twenty-first century" by the Harvard Business Review in 2012. With 79 years left in the century, it's reasonable to believe they'll reconsider. Nonetheless, Data Scientists are receiving a lot of attention right now, and publications about Data Science are flourishing as a result.

It would be pointless to add another book to the stack if it simply repeated or repackaged text that could be found elsewhere. However, while reviewing new data science literature, I noticed that most authors would rather explain how to use all of the latest tools and technologies than discuss the nuanced problem-solving nature of the data science process.

Even with several books and up-to-date knowledge of algorithms and data stores, many aspiring Data Scientists were left wondering, "Where do I begin?" As a result, here is yet another book on Data Science. This one, on the other hand, attempts to guide you through the data science process as a path with numerous forks and potentially unknown destinations.

The book forewarns you of what is to come, instructs you on how to prepare for it, and offers advice on how to deal with unexpected events. It discusses which tools are most useful and why, but the main goal is always to navigate the path the data science process intelligently, efficiently, and successfully, in order to arrive at practical solutions to real-world data-centric problems.

Apart from the fact that Data Science is one of the highest-paid and most popular fields of date, it is also important to note that it will continue to be more innovative and challenging for another decade or more. There will be enough data science jobs that can fetch you a handsome salary as well as opportunities to grow.

Having said this, nothing beats reading data science books to get started. This forced me to write a book to help people understand the fundamentals of Data Science as well as cutting-edge topics.

This accessible and classroom-tested text book presents an introduction to the fundamentals of the emerging and interdisciplinary field of Data Science. The coverage spans key concepts adopted from statistics and machine learning, and the practical application of Data Science for such tasks as building recommender systems or performing sentiment analysis.

Good luck with your studies!!!