Every tech book retold chapter by chapter.
Laura Funderburk's hands-on guide to building production-grade NLP and LLM pipelines with Haystack and LangGraph, covering RAG, tool contracts, context engineering, and agentic AI architecture.
Chisom Nwokwu's beginner-friendly guide to data engineering covering databases, SQL, pipelines, cloud platforms, and career building.
Adi Wijaya's practical guide to building scalable data pipelines and platforms using Google Cloud Platform services like BigQuery, Dataproc, Dataflow, and Cloud Composer.
Paul Crickard's hands-on guide to building data pipelines with Python, covering ETL, NiFi, Airflow, Kafka, Spark, and production deployment.
Stephen Mariadas and Ian Huke's beginner-friendly guide to data science covering the full lifecycle from problem definition to machine learning and AI.
Rick J. Scavetta and Boyan Angelov's guide to using Python and R together for modern data science instead of picking sides.