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Data science is a lucrative field with many prospects in the future. With the recent advancement of AI, it should not be surprising that data science would still become one of the most sought-after occupations. However, I know that it’s not an easy field to break through.
There is a lot of learning to do if you want to break into the data science field and understand many data aspects. It also means we need good material to learn as we don’t want to waste time. This article will discuss five cheap books you can use to master data science.
What are these books? Let’s get into it.
To master the field, we need to understand the field we want to undertake in depth. We need to understand data science to bring value to our work and avoid not getting the job at all.
The Data Science book by John D. Kelleher and Brendan Tierney could become your first step to understanding the overall data science industry. With a price of $9, you would learn the following from the book:
- Data Science History
- Data Science Applications
- The Tools of Data Science
- Ethical Concerns in Data Science Application
- Data Science Career Growth
This book is a great introductory book for anyone who wants to break into the data science field or understand the data science concept better.
Programming skills have already become the backbone of data scientists, and every company lists them as requirements. The requirement is often the Python language, the modern data scientists’ programming language. Without Python skills, there is a big chance we can’t do our job correctly.
Python Data Analysis book by Avinash Navlani, Armando Fandango and Ivan Idris (Author) would provide complete learning on navigating the data science field with the necessary Python skills. What you would learn includes:
- Core Python Libraries and Data Handling
- Statistical and Mathematical Foundations
- Advanced Data Analysis Techniques
- Specialized Data Analysis
- Computational Efficiency with Dask
The book price is around $16, which is in the cheaper range compared to the other books out there. Although, the value of this book is big.
While data scientists need to know programming language, we must also understand statistical theory. Our data analysis and machine learning algorithms were based on statistical methodology, and we needed to understand the basic statistics to understand the data activity we did.
Naked Statistics: Stripping the Dread from the Data, written by Charles Wheelan, breaks down statistical concepts in a fun way and with application examples. The book includes cases for:
- Standard Error and CI applications in political polls cases.
- Regression Analysis at risk of health problems in the UK.
- Netflix and Target statistical inferences applications for product recommendation.
There are still many statistical concepts you would learn from this book. With the price of $8, you can easily understand why statistics is important in data science.
After a basic understanding of data science, we should learn about the machine learning algorithm. The primary tool of data scientists is the ML model, and it’s essential to understand how each model works and why we are using them.
The Hitchhiker’s Guide to Machine Learning Algorithms by Devin Schumacher, Francis La Bounty Jr., and Devanshu Mahapatra would serve as a reference to understand the machine learning algorithm further. You will learn the following concepts from this book:
- Classification & Regression Techniques
- Clustering Algorithms
- Neural Networks and Deep Learning
- Optimization and Problem Solving Algorithms
- Ensemble Methods and Dimensionality Reduction Techniques
- Reinforcement Learning
Each chapter is a standalone section, so we can jump into any chapter we are interested in. At $12, you would get a lot of knowledge from the theoretical to the ML applications in the real world.
Data science is not only about programming, machine learning, or statistics. It’s all about delivering value from the data we have. It is then crucial for any data scientist to understand how to communicate our technical results in the insight that stakeholders or non-technical persons understand.
In the Data Insights Delivered book by Mo Villagran, she explains that data professionals struggle to deliver value due to poor communication with stakeholders, unrealistic expectations fueled by marketing hype, and the underutilization of most data products. With her experience, she composes seven steps that we can take to have better communication and assess the stakeholder’s needs.
At $15, you can learn all these steps quickly and improve yourself with the soft skills that are always required.
Data Science is a challenging field to break. That’s why these five cheap books will help you master data science. The books include:
- Data Science (The MIT Press Essential Knowledge series)
- Python Data Analysis
- Naked Statistics: Stripping the Dread from the Data
- The Hitchhiker’s Guide to Machine Learning Algorithms
- Data Insights Delivered
Cornellius Yudha Wijaya is a data science assistant manager and data writer. While working full-time at Allianz Indonesia, he loves to share Python and Data tips via social media and writing media.
