Data Science in 30 Days The Complete Beginner's Guide

With step-by-step lessons, real-world examples, and hands-on exercises, this book is perfect for those looking for a Python data science book that balances theory with practical applications. Whether you are a student, professional, or hobbyist, you'll find everything you need to get started with data science projects with Python and apply it in various domains such as business analytics, finance, artificial intelligence, and big data processing.
What You'll Learn in 30 Days:
✔ The fundamentals of data science, including data collection, cleaning, and preprocessing
✔ How to use Python, NumPy, Pandas, and MatDescriptionlib for Python for data science tasks
✔ Exploratory data analysis (EDA) techniques to uncover insights from data
✔ Introduction to statistics, probability, and hypothesis testing for data science for business applications
✔ Supervised and unsupervised machine learning models, including regression, classification, and clustering
✔ Working with databases, SQL queries, and big data tools like Apache Spark
✔ Advanced topics such as data science for finance, deep learning, NLP, time series analysis, and model deployment
Why This Book Stands Out:
✔ A structured day-by-day learning plan to keep you on track
✔ Practical exercises and coding challenges to reinforce each concept
✔ Covers both beginner and intermediate topics, making it ideal for continuous learning
✔ A bonus section with cheat sheets, common errors, and interview questions
If you're looking for the best Python data science book that breaks down complex concepts into digestible lessons, this book is for you. Whether you're interested in data science projects with Python, preparing for a data science bootcamp, or simply want to explore data science for business in an easy-to-understand manner, this book provides a complete, practical guide.

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