Solving Data Science Case Studies with Python

Improve Your Problem-Solving Skills in Data Science by Solving Case Studies.

Solving Data Science Case Studies with Python is an eBook written by Aman Kharwal. This book is specially written for those who know the basics of the Python programming language as well as the necessary Python libraries you need for data science like NumPy, Pandas, Matplotlib, Seaborn, Plotly, and Scikit-learn. You can easily get this ebook from here.

This book aims to teach you how to think while solving a business problem with your data science skills. To achieve the goal of this book, I started by giving you all the knowledge you need to have before you apply for your first data science job.

The technical skills and soft skills you need to become a Data Scientist are also discussed in this book. Next, you’ll find some of the best data science case studies that will help you understand what your approach should be while solving a business problem. Ultimately, you will also find some of the most important data science interview questions with their solutions. I hope this book will add a lot of value to your data science skills and that you will feel confident in your entire journey as a Data Scientist.

Download Solving Data Science Case Studies with Python (eBook)

Index of Solving Data Science Case Studies with Python

Below is the index of the book that may give you an idea about what you will get in this book:

1. For Whom This Book is For?
2. Why I Use Python For Data Science?
3. Skills You Need to Become a Data Scientist
4. Data Science Case Study 1
5. Data Science Case Study 2
6. Data Science Case Study 3
7. Data Science Case Study 4
8. Data Science Case Study 5
9. Data Science Interview Questions

Summary

I hope you like the ebook “Solving Data Science Case Studies with Python”. This book is specially written for those who know the basics of the Python programming language as well as the necessary Python libraries you need for data science like NumPy, Pandas, Matplotlib, Seaborn, Plotly, and Scikit-learn. Feel free to ask your valuable questions in the comments section below.