Master modern data flow automation and build powerful ETL pipelines with one of the most advanced data integration tools. This hands-on course teaches you how to design, process, and manage data flows using Apache NiFi. Gain real-world skills to handle big data, integrate multiple systems, and deploy scalable data solutions used in enterprise environments.

Master real-time data streaming with Kafka using industry-standard data contracts and schema management. This hands-on course teaches you how to build robust, scalable Kafka applications using AVRO and Schema Registry. You’ll gain practical skills to ensure data consistency, handle schema evolution, and develop production-ready systems.

Master Microsoft Fabric from the ground up and gain the advanced skills needed to build powerful data solutions across modern analytics platforms. This course delivers a practical, hands-on journey through data integration, pipelines, analytics, and governance, helping you become confident in designing and managing real-world data workflows.

Artificial intelligence has undergone rapid advancements, and Large Language Models (LLMs) are at the forefront of this revolution. This LLM book offers insights into designing, training, and deploying LLMs in real-world scenarios by leveraging MLOps best practices. The guide walks you through building an LLM-powered twin that’s cost-effective, scalable, and modular. It moves beyond isolated Jupyter notebooks, focusing on how to build production-grade end-to-end LLM systems. Throughout this book, you will learn data engineering, supervised fine-tuning, and deployment. The hands-on approach to building the LLM Twin use case will help you implement MLOps components in your own projects. You will also explore cutting-edge advancements in the field, including inference optimization, preference alignment, and real-time data processing, making this a vital resource for those looking to apply LLMs in their projects. By the end of this book, you will be proficient in deploying LLMs that solve practical problems while maintaining low-latency and high-availability inference capabilities. Whether you are new to artificial intelligence or an experienced practitioner, this book delivers guidance and practical techniques that will deepen your understanding of LLMs and sharpen your ability to implement them effectively.

PASS the Snowflake SnowPro Core Certification Exam (Unofficial)

Learn Microsoft Fabric with real-time data projects using Lakehouse, Dataflow Gen2, Fabric Notebooks & Power BI

Master SQL from scratch with MySQL, 4 job simulations, 4 resume-ready projects & smart AI-powered learning

This book presents volume 2 of selected research papers presented at the Second International Conference on Digital Technologies and Applications (ICDTA 22), held at Sidi Mohamed Ben Abdellah University, Fez, Morocco, on 28–29 January 2022. Highlighting the latest innovations in digital technologies as: Artifiscial Intelligence, Internet of things, Embedded systems, Network Technology, information processing and their applications in several areas as hybrid vehicles, renewable energy, Mechatronics, Medicine… The respective papers will encourage and inspire researchers, industry professionals, and policymakers to put these methods into practice.

A hands-on technical and industry roadmap for aspiring data engineers

This book provides state-of-art information on high-accuracy scientific computing and its future prospects, as applicable to the broad areas of fluid mechanics and combustion, and across all speed regimes. Beginning with the concepts of space-time discretization and dispersion relation in numerical computing, the foundations are laid for the efficient solution of the Navier-Stokes equations, with special reference to prominent approaches such as LES, DES and DNS. The basis of high-accuracy computing is rooted in the concept of stability, dispersion and phase errors, which require the comprehensive analysis of discrete computing by rigorously applying error dynamics. In this context, high-order finite-difference and finite-volume methods are presented. Naturally, the coverage also includes fundamental notions of high-performance computing and advanced concepts on parallel computing, including their implementation in prospective hexascale computers. Moreover, the book seeks to raisethe bar beyond the pedagogical use of high-accuracy computing by addressing more complex physical scenarios, including turbulent combustion. Tools like proper orthogonal decomposition (POD), proper generalized decomposition (PGD), singular value decomposition (SVD), recursive POD, and high-order SVD in multi-parameter spaces are presented. Special attention is paid to bivariate and multivariate datasets in connection with various canonical flow and heat transfer cases. The book mainly addresses the needs of researchers and doctoral students in mechanical engineering, aerospace engineering, and all applied disciplines including applied mathematics, offering these readers a unique resource.