Unlocking Data Science: A Comprehensive Review of Zeeshan Ul Hassan Usmani and Nisar Rassed's Must-Read Book!

Book Review

"Data Science," written by Zeeshan Ul Hassan Usmani and Nisar Rassed, is a comprehensive guide that offers readers a deep understanding of data science. The book is structured into sixteen chapters, each packed with valuable insights and practical knowledge about data science and its tools and techniques. If you're a beginner or considering a career in data science, this book is an excellent starting point.

"Data is the new oil." — This popular saying highlights the immense value of data in today's world, and this book aims to help you harness that value effectively.

The first chapter delves into the ideology of data science, explaining its significance in our daily lives and how its principles are applied across various fields. The second chapter emphasizes the importance of data-driven decision-making over-relying on gut feelings, using well-illustrated examples with graphs and images.

In the third chapter, the author discusses the everyday relevance of data science using unconventional but effective examples from cooking and business. These relatable scenarios make complex concepts easy to grasp for non-technical readers, maintaining their interest throughout.

Chapter four explores data science experiments, detailing the types of data science, their applications, and the appropriate analytical techniques for different types of research. Accurate results stem from understanding these techniques and their proper use.

Chapter five introduces the data science toolbox, showcasing tools like Microsoft Excel, R Studio, H2O, Orange, and Vita. Each tool is briefly explained, highlighting its relevance and application in data analysis.

The sixth chapter outlines the data science life cycle, presenting the steps involved graphically and explaining each step effectively. This chapter is crucial as it lays the groundwork for any data science project. The subsequent chapter provides a practical guide for building your first data science project, using Yahoo Finance as an example.

In chapter eight, the author moves on to the concept of big data, explaining the types of data available, the tools and techniques for handling it, and its growing importance in our lives.

The following chapters offer guidance on becoming a data scientist, detailing the pioneers in the field, the essential tools and techniques, and the platforms for learning them. Career opportunities, job roles, responsibilities, and salaries for data scientists are also covered, along with alternative earning options like part-time jobs, consultancy, and participation in international data science competitions.

Further chapters introduce various tools and platforms such as Kaggle, R, Python, H2O.ai, and Power BI. The author provides introductions, website links, installation guides, and information on essential libraries, as well as insights into Kaggle competitions and their benefits.

H2O, an open-source software, is highlighted for its ease of use without requiring extensive programming skills. The book thoroughly covers the basics of languages like Python and R, including variables and libraries.

In summary, I highly recommend "Data Science" to anyone interested in developing skills in data science or learning about the world of big data. Written in Urdu with an available English version, this book is a comprehensive collection of essential data science concepts. It's a valuable resource for anyone looking to dive into this field. Happy reading!