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[booksz]

Data Science with Python: From Zero to Machine Learning
English | 2025 | ISBN: 9798230222682 | Pages: 161 | EPUB (True) | 596.80 KB
Data Science with Python: From Zero to Machine Learning

?
Your Complete Guide to Mastering Data Science - No Experience Needed!
Want to break into the high-demand field of data science? This
all-in-one guide
takes you from
absolute beginner to machine learning pro
using Python - the #1 language for data science.
What You'll Learn:

Python Basics → ML Mastery:
Start coding in Python and progress to
building/deploying ML models

Key Libraries:
Master
NumPy, Pandas, MatDescriptionlib, Seaborn
for data analysis & visualization

Real-World Data Wrangling:
Clean, preprocess, and analyze data like a pro

Machine Learning Algorithms:
Regression, Classification, SVMs, Neural Networks & more

Deep Learning:
Build AI models with
TensorFlow & Keras

Model Deployment:
Learn to
put your models into production

Ethics & Best Practices:
Responsible AI development
Perfect For:
✔ Aspiring data scientists
✔ Developers transitioning into AI/ML
✔ Analysts looking to upskill
✔ Anyone who wants a
job-ready data science portfolio
?
By the End, You'll Be Able To:
*
Analyze big datasets
with Python
*
Train ML models
that make predictions
*
Visualize insights
like a pro
*
Deploy solutions
that businesses use
?
Why This Book?
Zero to Advanced
- No prior experience needed
Hands-On Projects
- Learn by doing
Industry-Ready Skills
- Covers what employers want
Latest Tools
- Updated for the newest tools
Start Your Data Science Journey Today!

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[booksz]

Data Science with Python: Unlocking the Power of Pandas and Numpy
English | 2024 | ISBN: B0DL3QXBYP | Pages: 373 | EPUB (True) | 436.48 KB
"Data Science with Python: Unlocking the Power of Pandas and Numpy" is an essential guide for beginners and professionals alike, striving to master the art of data analysis using Python's robust ecosystem. This book delves into the foundational aspects of data science, providing readers with a comprehensive understanding of how to harness Python's capabilities for data manipulation and exploration. By covering key libraries such as Pandas and Numpy, it equips readers with the skills necessary to perform high-performance numerical computations and sophisticated data analysis tasks.

Structured to ensure a seamless learning experience, this book introduces essential Python programming concepts and progressively advances to more complex topics in data cleaning, preprocessing, and visualization. Each chapter is crafted to build upon the last, ensuring a coherent progression and a deepening of knowledge. With a series of practical projects, readers will gain hands-on experience in real-world data science applications, learning how to develop predictive models and deploy solutions effectively. Through this approach, the book bridges the gap between theoretical understanding and practical application, empowering readers to unlock the full potential of data science in today's data-driven landscape.

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Data Structures & Algorithms for AI: Building Smart Systems (AI from Scratch : Step-by-Step Guide to Mastering Artificial Intelligence Book 3)
English | 2025 | ASIN: B0DVSK4LTZ | 423 pages | Epub | 1.85 MB
AI from Scratch: Step-by-Step Guide to Mastering Artificial Intelligence (Book 3)

Artificial Intelligence (AI) is transforming industries, from healthcare to finance, robotics to real-time decision-making. But what makes AI models truly efficient? The answer lies in data structures and algorithms-the backbone of AI performance, scalability, and optimization.
Data Structures & Algorithms for AI: Building Smart Systems is a comprehensive guide designed to help AI engineers, machine learning practitioners, and software developers master the core computational techniques that power modern AI systems. As the third book in the AI from Scratch series, this volume takes a deep dive into the computational foundations necessary to build fast, scalable, and intelligent AI solutions.
What You'll Learn:
How arrays, linked lists, trees, graphs, and hash tables impact AI efficiency
Graph algorithms, reinforcement learning, and heuristic search for AI applications
Sorting, dynamic programming, and metaheuristics to optimize AI performance
Deep learning data structures, parallel computing, and real-time AI systems
AI-ready probabilistic data structures for handling large-scale and streaming data
Why This Book?
Unlike traditional algorithm books, which focus on generic applications, this book is tailored for AI professionals. You'll learn how to implement AI-driven data structures with a focus on speed, memory optimization, and scalability. From neural network optimizations to AI-powered search techniques, this book provides the computational toolkit needed for building high-performance AI applications.
Who Should Read This Book?
AI & Machine Learning Engineers optimizing model performance
Data Scientists looking for AI-focused algorithmic techniques
Software Developers implementing AI-based applications
Researchers & Students wanting a deep dive into AI-specific data structures
With real-world case studies, hands-on examples, and AI-specific optimizations, this book ensures that you don't just learn how data structures and algorithms work-but how to apply them to build smarter AI systems.

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[booksz]

Data Structures & Algorithms With Golang 101
English | 2024 | ASIN: B0DKTP6JMK | 280 pages | Epub | 226.71 KB
Why Data Structures and Algorithms?

Data structures and algorithms are the backbone of efficient problem-solving in computer science. They enable developers to organize, store, and manipulate data effectively, making applications faster, more scalable, and resource-efficient. From search engines to social media platforms, every modern technology leverages the power of DSA. Mastering DSA not only sharpens analytical thinking but also prepares developers to tackle complex challenges, making it a must-have skill for coding interviews and real-world projects.
Why Golang for DSA?
Golang, or Go, is a modern programming language known for its simplicity, performance, and efficiency. Designed by Google, Go excels in handling concurrent tasks, making it ideal for modern software solutions. Its clean syntax, built-in garbage collection, and robust standard library simplify complex implementations, including DSA. For beginners and professionals alike, Go provides a balanced learning curve and real-world applicability, making it a perfect language to explore DSA concepts.
About the Book
This book bridges the gap between theory and practice, combining foundational DSA concepts with practical Golang implementations. Each chapter offers clear explanations, hands-on examples, and real-world applications, ensuring a seamless learning experience. Whether you're preparing for interviews or building scalable systems, this book will empower you to solve problems with confidence and efficiency.
About the Publisher
101 Book is a forward-thinking company dedicated to democratizing access to quality education by offering affordable learning materials. With a mission to empower learners globally, the company designs and distributes high-quality books, courses, and educational resources at exceptionally low prices. Focused on inclusivity and innovation, 101 Book ensures its products cater to diverse subjects, age groups, and learning needs. By leveraging cost-efficient production methods without compromising content quality, the company bridges the education gap, enabling millions to achieve academic success. Committed to excellence and accessibility, 101 Book is reshaping the landscape of affordable education, fostering knowledge for all.

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[booksz]

Data Structures and Algorithms for Beginners
English | 2024 | ISBN: 2940180884848 | Pages: 125 | EPUB (True) | 271.09 KB
Embark on your journey into the world of computing with "Data Structures and Algorithms for Beginners: A Beginner's Guide to Essential Concepts and Techniques." This book is expertly crafted to guide beginners through the fundamental principles that form the backbone of computer science. Whether you are a novice looking to delve into programming, a student preparing for your computer science courses, or a professional aiming to refresh your knowledge, this guide provides an essential foundation in data structures and algorithms.

"Data Structures and Algorithms for Beginners" demystifies complex topics with clear explanations, real-world examples, and practical exercises. Starting from the basics, you'll learn about different types of data structures, from simple arrays and linked lists to more intricate structures like trees and graphs. As you progress, you'll explore the mechanics and strategies of efficient algorithms, understanding how they manipulate and process data to solve problems.
This guide also dives into the critical aspect of algorithm analysis, teaching you how to evaluate the performance of an algorithm through concepts like time and space complexity. You'll gain hands-on experience with sorting and searching algorithms, discovering how they are applied in various applications and how they can be optimized for speed and efficiency.
Each chapter includes practical code examples in a beginner-friendly programming language, step-by-step walkthroughs, and illustrative diagrams to help solidify your understanding. By the end of this book, you will have a solid grasp of key concepts and be well-prepared to apply these techniques in practical scenarios, from software development to preparing for technical interviews.
Step into the world of computer science with confidence and curiosity! "Data Structures and Algorithms for Beginners" is your comprehensive guide to mastering these critical concepts, opening doors to a multitude of possibilities in technology and beyond.

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[booksz]

Data Structures and Algorithms for Beginners
English | 2024 | ISBN: 2940179945109 | Pages: 95 | EPUB (True) | 489.71 KB
Embark on a transformative journey into the heart of problem-solving with "Data Structures and Algorithms for Beginners." Tailored for beginners, this comprehensive guide unravels the complexities of data structures and algorithms, turning what may seem daunting into an exciting exploration of logical thinking and efficient computation.

In the opening chapters, readers are gently introduced to the fundamental concepts, laying a solid foundation for the exciting adventure ahead. What are data structures, and why do algorithms matter? The book answers these questions and more, making the seemingly abstract world of computer science tangible and accessible.
Explore the core data structures such as arrays, linked lists, trees, and graphs, and grasp the essence of algorithmic paradigms like divide and conquer, greedy algorithms, and dynamic programming. The journey continues with practical applications, from searching and sorting to graph algorithms, offering readers a real-world perspective on how these concepts are utilized in solving everyday problems.
The book is not just a theoretical guide; it's a hands-on experience. With clear explanations, pseudocode, and flowcharts, readers will be empowered to tackle problems with confidence. Dive into case studies, examine problem-solving strategies, and discover the art of breaking down complex issues into manageable parts.
"Data Structures and Algorithms for Beginners" doesn't stop at the basics. Advanced topics like hashing, trie data structures, and complexity analysis are unveiled, giving readers a glimpse into the depth and breadth of the field. The journey concludes with invaluable tips for interview preparation, ensuring that readers are well-equipped to showcase their newfound knowledge in a professional setting.
Let the pages guide you through the maze of data structures and algorithms, transforming challenges into triumphs. Unlock the power of logical thinking and efficient problem-solving with "Data Structures and Algorithms for Beginners." Your journey begins now.

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Data Structures And Algorithms Made Easy: Data Structures And Algorithmic Puzzles
English | 2023 | ASIN: B0CBW278NC | Pages not found | PDF | 13.82 MB
"Data Structures And Algorithms Made Easy: Data Structures and Algorithmic Puzzles" is a book that offers solutions to complex data structures and algorithms. It can be used as a reference manual by those readers in the computer science industry. This book serves as guide to prepare for interviews, exams, and campus work. In short, this book offers solutions to various complex data structures and algorithmic problems.

Topics Covered:
Introduction
Recursion and Backtracking
Linked Lists
Stacks
Queues
Trees
Priority Queue and Heaps
Disjoint Sets ADT
Graph Algorithms
Sorting
Searching
Selection Algorithms [Medians]
Symbol Tables
Hashing
String Algorithms
Algorithms Design Techniques
Greedy Algorithms
Divide and Conquer Algorithms
Dynamic Programming
Complexity Classes
Miscellaneous Concepts

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[booksz]

Data Structures and Algorithms with Python
English | 2024 | ISBN: 2940180480200 | Pages: 120 | EPUB (True) | 342.85 KB
Dive into the world of data structures and algorithms with this comprehensive guide tailored for Python programmers. "Data Structures and Algorithms with Python: Elevating Your Coding Skills with Data Structures and Algorithms" is an essential resource for anyone looking to deepen their understanding of computational methods and enhance their problem-solving skills.

Starting with the basics of Python and progressing through to complex data structures and algorithmic techniques, this book offers a structured approach to learning. It not only demystifies the theoretical aspects of the topics but also provides practical implementations and real-world applications, ensuring that readers gain hands-on experience.
Key Features:
Comprehensive Coverage:
From basic data types and control structures in Python to advanced topics like graph algorithms and dynamic programming, this book covers a wide range of fundamental and complex concepts.
Hands-On Learning:
Each chapter includes Python code examples, exercises, and challenges that encourage active participation and reinforce learning.
Complexity Analysis:
Understand how to evaluate the efficiency of algorithms and data structures using Big O notation, enabling you to select the most appropriate tool for your coding projects.
Real-World Applications:
Discover how data structures and algorithms are applied in various fields such as web development, data analysis, machine learning, and more, through case studies and projects.
Resources for Further Learning:
An extensive list of resources, including books, online courses, and tutorials, is provided to support continued learning and exploration beyond the book.
"Data Structures and Algorithms with Python" is more than just a book; it's a pathway to enhancing your coding expertise, improving your analytical thinking, and solving complex computational problems with confidence. Embark on this educational journey to unlock new possibilities in your programming career or hobbyist endeavors.

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[booksz]

Data Structures in Python
English | 2024 | ISBN: 2940180692948 | Pages: 120 | EPUB (True) | 463.05 KB
Unlock the power of Python with

"Data Structures in Python,"
a comprehensive guide designed for both beginners and experienced programmers. This book provides a clear and engaging exploration of data structures, offering you the tools and techniques to implement them effectively in real-world applications.
From fundamental concepts like lists, tuples, and dictionaries to more advanced structures such as trees, graphs, and hash tables, this guide breaks down complex topics into easily digestible sections. Each chapter features practical examples, hands-on exercises, and illustrative diagrams to reinforce your understanding and help you apply what you've learned.
In addition to covering essential data structures, this book emphasizes best practices for choosing the right structure for specific problems, optimizing performance, and enhancing your algorithms. You'll discover how to analyze time and space complexity, ensuring your code is efficient and scalable.
"Data Structures in Python"
serves as your go-to resource. Join the journey of mastering data structures, and empower yourself to tackle real-world challenges with confidence and creativity.

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Data Warehouse Essentials: Mastering the Foundations of Data Management
English | 2025 | ISBN: B0F2N4QL5J | Pages: 196 | EPUB (True) | 1.44 MB
Data Warehouse Essentials is a comprehensive course designed to empower individuals with a robust understanding of data warehousing concepts, architecture, and best practices. Whether you're an aspiring data professional or looking to improve your data management skills, this course provides the essential knowledge needed to design, implement, and optimize a data warehouse effectively.

Master the Fundamentals of Data Warehousing Understand core data warehousing concepts and their importance in modern data management. Gain insights into key architectural components and design considerations. Learn data modeling techniques, including ER models and star schemas. Explore the essentials of ETL processes and integrating multiple data sources. Discover popular data warehousing tools and technologies. Develop skills for querying, reporting, and optimizing data warehouse performance. Ensure security, compliance, and governance in data warehousing. Identify the relationship between big data and data warehouses.
Comprehensive Guide to Data Warehousing Concepts and Techniques
This course begins with an introduction to data warehousing, providing an overview of its fundamental concepts, highlighting the significant impact they have in today's data-driven decision-making processes. Students will delve into the architecture of data warehouses, examining key components and the various design considerations crucial for creating efficient systems.
As learners progress, they will explore data modeling techniques, including Entity-Relationship (ER) models and star schemas, which are integral for organizing and structuring data within a warehouse. The course further covers essential ETL (Extract, Transform, Load) procedures necessary for data integration and cleansing, ensuring a smooth and accurate data flow into the warehouse.
The practical skills taught extend to the use of popular data warehousing tools and technologies, aiding students in navigating the current technology landscape. Additionally, the course addresses the critical areas of querying and reporting, providing techniques for effective data analysis and visualization.
Individuals will gain insights into performance optimization strategies, essential for maintaining the efficiency and speed of data warehouse operations. Furthermore, the course emphasizes security and data governance, critical for ensuring that data warehouses meet compliance requirements and remain secure.

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[booksz]

Data-Driven Cybersecurity (MEAP V05) by Mariano Mattei
English | 2025 | ISBN: 9781633436107 | 470 pages | PDF,EPUB | 24.62 MB
Measure, improve, and communicate the value of your security program.

Every business decision should be driven by data-and cyber security is no exception. In Data-Driven Cybersecurity, you'll master the art and science of quantifiable cybersecurity, learning to harness data for enhanced threat detection, response, and mitigation. You'll turn raw data into meaningful intelligence, better evaluate the performance of your security teams, and proactively address the vulnerabilities revealed by the numbers.
Data-Driven Cybersecurity will teach you how to:
Align a metrics program with organizational goals
Design real-time threat detection dashboards
Predictive cybersecurity using AI and machine learning
Data-driven incident response
Apply the ATLAS methodology to reduce alert fatigue
Create compelling metric visualizations
Data-Driven Cybersecurity teaches you to implement effective, data-driven cybersecurity practices-including utilizing AI and machine learning for detection and prediction. Throughout, the book presents security as a core part of organizational strategy, helping you align cyber security with broader business objectives. If you're a CISO or security manager, you'll find the methods for communicating metrics to non-technical stakeholders invaluable.
about the book
Data-Driven Cybersecurity shows you the metrics, data, and KPIs that will help you assess and enhance the performance of your cyber security programs. You'll learn how to turn complex metrics into actionable security practices, following the unique ATLAS (Alert Threshold Lifecycle Assessment System) methodology created by author Mariano Mattei. You'll go hands-on to build a real-time threat detection dashboard, and discover how AI and machine learning can proactively predict cybersecurity incidents. Case studies, interactive exercises, templates for KPIs, and expert insights help illustrate each new concept.

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Data-Driven Decision Support System in Intelligent HealthCare
by Bhattacharyya, Debnath;Hu, Yu-Chen;, Yu-Chen Hu
English | 2025 | ISBN: 1032806273 | 272 pages | True EPUB | 11.73 MB

Machine Intelligence with Generative AI is one of the most trending topics with applications in almost all fields of life. In healthcare, it is not only accelerating the development of new products, but also automating the generation of new and synthetic content making it easier to train and improve machine learning models. Some of the biggest achievements of Generative AI in healthcare have been drug discovery, personalized care, differentially private synthetic data generation, operational efficiency, and many more. Generative AI models like Generative Adversarial Networks, and Variational Autoencoders are employed to generate synthetic medical images, aiding in data augmentation, facilitating disease diagnosis, and enabling advanced medical imaging research. Additionally, Generative AI techniques are being utilized for creating realistic electronic health records (EHRs) and simulated patient data, supporting privacy-preserving data sharing, and empowering innovative studies for personalized medicine and drug development. NLP models like ClinicalBERT use transformer-based deep learning architecture to understand and represent contextual information in large clinical text datasets, such as electronic health records (EHRs) and medical literature, and can better grasp medical terminologies, domain-specific language, and contextual nuances that are unique to the healthcare field. This volume delves into the realm of Machine Intelligence with Generative AI and explores its impact on the healthcare industry.Generative AI is one of the most trending topics and application in every field of Science and Engineering with AI and Machine Intelligence. It is used to develop new products and automate the system by generating the new and improved models and improve decision making systems.

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Data-Intensive Applications: Design, Development, and Deployment Strategies for Scalable and Reliable Systems
English | 2024 | ISBN: 2940179805403 | Pages: 120 | EPUB (True) | 538.00 KB
"Data-Intensive Applications: Design, Development, and Deployment Strategies for Scalable and Reliable Systems" is a comprehensive guide to building robust and scalable applications in the era of big data. With the explosion of data in recent years, building applications that can handle massive amounts of data has become increasingly important. This book covers the entire lifecycle of data-intensive applications, from designing and developing the application to deploying it in a production environment.

The book begins with an introduction to the challenges and opportunities of building data-intensive applications. It then moves on to cover the key concepts and technologies used in building these applications, including distributed systems, data processing frameworks, and storage technologies. The book also covers best practices for designing and developing data-intensive applications, including how to handle data at scale, how to ensure reliability and fault tolerance, and how to optimize performance.
In addition, the book covers the deployment and management of data-intensive applications, including strategies for deploying applications in the cloud, managing infrastructure, and monitoring and debugging applications in production. The book also includes case studies and real-world examples from companies that have successfully built and deployed data-intensive applications.
Whether you are a software engineer, data scientist, or IT professional, this book will provide you with the knowledge and skills you need to build and deploy data-intensive applications that are scalable, reliable, and performant.

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Data-Oriented Design for Games (MEAP V04) by Nitzan Wilnai
English | 2025 | ISBN: 9781633435612 | 287 pages | PDF,EPUB | 24.78 MB
Use Data-Oriented Design to deliver games with outstanding performance while using less time and resources.

Data-Oriented Design (DOD) has become standard practice for AAA games and indie devs who need to squeeze every drop of performance out of hardware and deliver games on a rapid schedule. DOD is a programming practice that streamlines the way your code accesses, stores, and uses data, taking advantage of modern CPU architecture and accelerating the dev process. Data-Oriented Design for Games is a unique and comprehensive guide to architecting and coding games using DOD principles.
In Data-Oriented Design for Games you'll learn:
Data-Oriented Design and its application to game development
Optimize performance on modern CPU architecture
Reduce complexity by separating data from logic
Improve code extensibility through data-first problem solving
The Entity Component System (ECS) and its relationship to DOD
Implement DOD in Unity and other object-oriented engines
Modern games need to be smooth, high-framerate experiences with deep gameplay that keeps users hooked for years. Data-oriented design takes advantage of modern CPUs to upgrade game performance, easily outpacing traditional object-oriented programming. DOD uses arrays instead of objects, avoids design patterns and subroutines, and utilizes pure atomic functions as much as possible. Plus, because you're only thinking about data and logic, DOD-games take less manpower and time than building with OOP. Data-Oriented Design for Games reveals how you can bring this powerful programming approach to your own projects. You'll discover both the essential theory behind DOD, and put it into practice to develop a complete game project.
about the book
Data-Oriented Design for Games teaches you to deliver high-performance games, with code that's simpler to extend and maintain. You'll learn to design games from scratch using DOD and also how to apply DOD to existing object-oriented codebases. Through a simulated development process-complete with Jira tickets-you'll construct a complete "survivor" style game that runs at a high framerate on limited hardware while being easy to expand. The book is fully illustrated with Unity architectural examples, diagrams, and engaging war stories from author Nitzan Wilnai's 20+ year career, punctuated by helpful sidebars that dispel DOD myths.

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[booksz]

Database and Framework project in Python: build modern web applications with a Python framework
English | 2023 | ASIN: B0C2C5FN7H | 372 pages | Epub | 3.38 MB
Python is a popular and influential high-level programming language widely used by beginners and professionals. It is known for its simplicity and readability, making it an ideal language for those just starting to learn to program.

In this book you will learn:
1. Digging Deeper Into Django Migrations
2. Use Redis With Python
3. Create an Index in Django Without Downtime
4. Django Migrations
5. Efficient Caching in Distributed Applications
6. Building a Simple Web App
7. Getting Started with Django Channels
8. Caching in Django With Redis
9. AWS Elastic Beanstalk
10. A Web Service Application Comparison
11. Fun with Django's New Postgres Features
12. Deploying a Django
13. Web Scraping with Scrapy and MongoDB
14. Web Scraping and Crawling
15. Handling Email Confirmation During Registration
16. Implementing a Redis Task Queue
17. Setting up Postgres, SQLAlchemy, and Alembic
18. A Simple Todo List Powered by Flask and RethinkDB
19. Migrating from SQLite to MySQL
20. Introduction to Python SQL Libraries
Overall, Python is an excellent choice for anyone who wants to learn programming, whether you're interested in web development, data analysis or want to learn a new skill. With its simplicity, readability, and versatility, Python is an excellent language to start your programming journey.

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Database Design with SQL: Building Fast and Reliable Systems
English | 2024 | ISBN: B0DL3ZZC2S | Pages: 425 | EPUB (True) | 494.60 KB
"Database Design with SQL: Building Fast and Reliable Systems" is an essential resource for beginners eager to master the fundamentals of database management and SQL. This comprehensive guide demystifies the core principles of database systems, providing readers with the knowledge to design efficient data architectures and execute complex SQL operations. Covering everything from basic data structures to advanced query optimization, the book equips learners with the crucial skills needed to build and manipulate robust databases that meet modern demands.

The book delves into the intricacies of relational databases and normalization, offering practical insights into data modeling and schema design. Readers will explore the power of SQL in both data retrieval and manipulation, progressing through foundational commands to sophisticated techniques like dynamic SQL and window functions. Additionally, the text addresses critical aspects of database security, transactions, and concurrency control, ensuring that systems remain resilient and secure in multi-user environments.
Beyond relational databases, "Database Design with SQL" introduces the versatile world of NoSQL and its role in big data, enabling learners to handle diverse data types and high-volume datasets. Through real-world case studies and best practices for database administration, this guide offers valuable strategies for maintaining performance and reliability. Whether you are embarking on a career in database management or seeking to enhance your technical expertise, this book is your gateway to mastering database design and SQL with confidence.

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[booksz]

Databricks Certified Data Engineer Associate Study Guide: In-Depth Guidance and Practice
English | 2025 | ISBN: 1098166833 | 408 pages | PDF | 25.51 MB
Data engineers proficient in Databricks are currently in high demand. As organizations gather more data than ever before, skilled data engineers on platforms like Databricks become critical to business success. The Databricks Data Engineer Associate certification is proof that you have a complete understanding of the Databricks platform and its capabilities, as well as the essential skills to effectively execute various data engineering tasks on the platform.

In this comprehensive study guide, you will build a strong foundation in all topics covered on the certification exam, including the Databricks Lakehouse and its tools and benefits. You'll also learn to develop ETL pipelines in both batch and streaming modes. Moreover, you'll discover how to orchestrate data workflows and design dashboards while maintaining data governance. Finally, you'll dive into the finer points of exactly what's on the exam and learn to prepare for it with mock tests.
Author Derar Alhussein teaches you not only the fundamental concepts but also provides hands-on exercises to reinforce your understanding. From setting up your Databricks workspace to deploying production pipelines, each chapter is carefully crafted to equip you with the skills needed to master the Databricks Platform. By the end of this book, you'll know everything you need to ace the Databricks Data Engineer Associate certification exam with flying colors, and start your career as a certified data engineer from Databricks!
You'll learn how to:
Use the Databricks Platform and Delta Lake effectively
Perform advanced ETL tasks using Apache Spark SQL
Design multi-hop architecture to process data incrementally
Build production pipelines using Delta Live Tables and Databricks Jobs
Implement data governance using Databricks SQL and Unity Catalog
Derar Alhussein is a senior data engineer with a master's degree in data mining. He has over a decade of hands-on experience in software and data projects, including large-scale projects on Databricks. He currently holds eight certifications from Databricks, showcasing his proficiency in the field. Derar is also an experienced instructor, with a proven track record of success in training thousands of data engineers, helping them to develop their skills and obtain professional certifications.

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[booksz]

Databricks Data Engineer Certification Guide: Pass the Associate Exam with Spark, Delta Lake & Streaming Mastery
English | 2025 | ISBN: B0F2NZ6JYL | Pages: 260 | Epub | 728.15 KB
Master the Databricks Data Engineer Certification - with Confidence

Looking to validate your data engineering skills and pass the Databricks Certified Data Engineer Associate exam? This practical and comprehensive guide walks you through every concept you need - from Spark and Delta Lake to structured streaming and pipeline orchestration.
Designed for beginners and professionals alike, this book simplifies the technical details and prepares you with a clear, exam-focused approach.
What you'll learn inside:
Understand the Databricks Lakehouse Platform and its core tools
Work with Spark: transformations, actions, joins, aggregations, and optimizations
Build real-time data pipelines using Structured Streaming
Manage and optimize Delta Lake tables with ACID transactions
Orchestrate production-grade jobs and workflows in Databricks
Navigate the Databricks UI, CLI, Repos, Unity Catalog, and job configurations
Get hands-on with mock exams and sample questions aligned to the exam objectives
Ideal for:
Aspiring data engineers
Data professionals transitioning into the Databricks ecosystem
Engineers preparing for the Databricks Associate Certification Exam
Developers, analysts, or data scientists seeking a structured path into data engineering
Whether you're targeting certification or simply want to become fluent in one of the most powerful data platforms today, this book is your companion to prepare, practice, and perform at your best.

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Dataproc Administration and Engineering Solutions: Definitive Reference for Developers and Engineers

English | 2025 | ASIN : B0D6X744V7 | 216 pages | EPUB | 206 MB

Unlock the full potential of Google Cloud Dataproc with "Dataproc Administration and Engineering Solutions," a comprehensive guide designed for cloud architects, data engineers, and platform administrators. This book offers an in-depth exploration of Dataproc's core architecture, detailing best practices for designing, provisioning, and optimizing scalable clusters that integrate seamlessly with the Hadoop ecosystem. From mastering high availability and security to leveraging advanced storage patterns and resource management, readers are equipped to build robust, cost-efficient cloud analytics platforms.
Delve into advanced job engineering and workflow orchestration, discovering flexible and automated approaches for deploying Spark and Hadoop jobs through APIs, templates, and workflow scheduling tools like Airflow and Dataproc Workflows. The book provides actionable insights on monitoring, troubleshooting, and performance optimization, ensuring reliability and efficiency for both batch and real-time data processing needs. Readers will also find practical guidance on running distributed machine learning pipelines and implementing resilient, fault-tolerant data infrastructures.

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David Busch's Nikon Z6 III Guide to Digital Photography
English | 2024 | ISBN: B0DM53T3PK | Pages: 522 | EPUB (True) | 21.56 MB
David Busch's Nikon Z6 III Guide to Digital Photography

is your all-in-one comprehensive resource and reference for the Nikon Z6 III, the company's next-generation enthusiast mirrorless camera
.
Equipped with the world's first partially-stacked CMOS sensor, this 24.5MP camera shares many of the advanced photography features of Nikon's top tier Z9 and Z8 flagship cameras, including a pre-capture feature that records action that happened
before
you clicked the shutter - at up to 120 frames per second. An enhanced vibration reduction feature offers up to 8 stops of stabilization linked to the active autofocus point for superb low-light and long lens photography.
Add cutting-edge video features that include 6K/60p internal RAW recording, 10X slow-motion capture, and in-line audio. and you'll see why photographers and videographers are so excited about the Nikon Z6 III. With this book in hand, you'll master all these impressive features, and fine tune your camera skills as you develop your creativity while taking great photographs with your new Z6 III.
Filled with detailed how-to steps and full-color illustrations,
David Busch's Nikon Z6 III Guide to Digital Photography
covers the cameras' photography capabilities in depth, from taking your first photos through advanced details of setup, exposure, lens selection, lighting, and more, and relates each feature to specific photographic techniques and situations. A handy visual guide to the Z6 III offers close-up photos and descriptions of the cameras' essential features and controls. Learn when to use each option and, more importantly, when
not
to use them, by following the author's recommended settings for every menu entry.
With best-selling photographer and mentor David Busch as your guide, you'll quickly have full creative mastery of your camera's capabilities, whether you're shooting on the job, as an advanced enthusiast, or are just out for fun. Start building your knowledge and confidence, while bringing your vision to light with the Nikon Z6 III today.

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