Software Engineering for Data Scientists 1st Edition

Software Engineering for Data Scientists, 1st Edition by Catherine Nelson is a practical, modern guide that bridges the gap between data science experiments and production-grade software. Clear, actionable, and written for practitioners, this book teaches the engineering habits that make models reliable, reproducible, and scalable.

You’ll discover essential software engineering principles tailored for data work: version control and collaboration, modular code design, testing and validation, CI/CD pipelines, deployment strategies, monitoring, and maintainability. Catherine Nelson blends real-world examples with step-by-step workflows so readers can move from prototype notebooks to robust services without losing speed or insight.

Designed for data scientists, ML engineers, analysts, and team leads across startups and enterprises—whether in North America, Europe, Asia, or beyond—this 1st Edition emphasizes best practices that apply globally. Learn how to reduce technical debt, improve reproducibility, accelerate model delivery, and communicate effectively with engineering teams.

What you gain: cleaner codebases, repeatable experiments, smoother handoffs, and greater confidence in production systems. The book balances theory and hands-on advice, making it ideal for self-study or as a reference on the job.

If you’re ready to elevate your data projects from exploratory scripts to maintainable systems, Software Engineering for Data Scientists by Catherine Nelson is the roadmap. Order your copy today and start building data Books that scale, endure, and deliver measurable value.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.