Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, Edition 2

The Art of Statistics: Learning from Data

Naked Statistics: Stripping the Dread from the Data

Fundamentals of Data Engineering: Plan and Build Robust Data Systems

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations

Introduction to Machine Learning with Python: A Guide for Data Scientists

Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

Dataclysm: Love, Sex, Race, and Identity--What Our Online Lives Tell Us about Our Offline Selves

Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter, Edition 3

Marketing Metrics: The Definitive Guide to Measuring Marketing Performance, Edition 2

Statistics For Dummies: Edition 2

What Is Data Science?

Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets

Deep Learning for Coders with fastai and PyTorch

How to Lie with Statistics

Beyond the Basic Stuff with Python: Best Practices for Writing Clean Code

Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh

Practical Lakehouse Architecture: Designing and Implementing Modern Data Platforms at Scale

Crack Python The Easy Way