Data Structures and Program Design Using Python. A Self-Teaching Introduction to Data Structures and Python

Mercury Learning and Information, D. Malhotra, N. Malhotra

This book, part of the Pocket Primer series, introduces the basic concepts of data science using Python 3 and other applications. It offers a fast-paced introduction to data analytics, statistics, data visualization, linear algebra, and regular expressions. The book features numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available.Understanding data science is crucial in today's data-driven world. This book provides a comprehensive introduction, covering key areas such as Python 3, data visualization, and statistical concepts. The practical code samples and hands-on approach make it ideal for beginners and those looking to enhance their skills.The journey begins with working with data, followed by an introduction to probability, statistics, and linear algebra. It then delves into Python, NumPy, Pandas, R, regular expressions, and SQL/NoSQL, concluding with data visualization techniques. This structured approach ensures a solid foundation in data science.

Pandas Basics. Mastering Data Analysis with Pandas

Mercury Learning and Information, Oswald Campesato

This book is essential for aspiring data scientists and anyone needing to perform data cleaning using Pandas and NumPy. It offers numerous code samples and comprehensive coverage of NumPy and Pandas features, including writing regular expressions. Chapter 3 introduces fundamental statistical concepts, while Chapter 7 delves into data visualization using Matplotlib and Seaborn. Companion files with code are available for download from the publisher.Starting with an introduction to Python, the course progresses through working with data, and then moves into Pandas, covering its functionalities in three detailed chapters. The statistical concepts provided are crucial for analyzing data effectively, while the visualization techniques enhance the ability to present data insights clearly.By the end of this course, users will have a solid foundation in data manipulation and cleaning, statistical analysis, and data visualization, enabling them to tackle real-world data science tasks confidently and efficiently.

Microsoft Excel 2021 Programming Pocket Primer. A Comprehensive Guide to Mastering Excel VBA

Mercury Learning and Information, Julitta Korol

This book, part of the successful Pocket Primer series, is designed for those who need to quickly master Excel programming fundamentals. It offers a concise, efficient introduction to VBA, ensuring you only learn what you need to feel comfortable with Excel VBA. The concepts learned in this book also apply to Access programming. The nine chapters progressively introduce you to programming in Microsoft Excel 2021.Starting with a quick guide to Excel macros and the VBA programming environment, the book moves on to fundamental concepts and writing function procedures. You will learn to add decision-making capabilities and looping statements to your programs, store and manage multiple values using arrays and collections, and utilize built-in tools for testing and debugging your code.By the end of the course, you will have a solid foundation in Excel VBA, enabling you to automate tasks and enhance your productivity. This structured approach makes the book an essential resource for mastering Excel VBA efficiently and effectively.

Java for Developers Pocket Primer. A Concise Guide to Mastering Java Programming

Mercury Learning and Information, Oswald Campesato

As part of the best-selling Pocket Primer series, this book offers a thorough introduction to Java development for beginners. It provides a fast-paced overview of core Java concepts and APIs, using Java 8 code samples. Companion files with source code are included.The journey begins with an introduction to Java, covering Boolean logic, Unicode, and user input. It progresses through methods, constructors, loops, arrays, and recursion. The course then delves into object-oriented programming (OOP) concepts and data structures. Advanced topics include streams, file handling, and integrating Java with SQL. The book also lists new features from Java 9 to Java 13.Understanding these concepts is crucial for developing efficient Java applications. This book transitions readers from basic to advanced Java programming, blending theoretical knowledge with practical skills. Companion files enhance the learning experience, making this book an essential resource for mastering Java development.

Industrial Automation and Robotics. A Comprehensive Guide to Automated Systems and Robotics

Mercury Learning and Information, Jean Riescher Westcott, A.K. Gupta, S.K. Arora

This course offers an introduction to automation and robotics for industrial applications. It begins with essential concepts of hydraulics and pneumatics, explaining their roles in industrial automation. Next, it delves into circuits and their applications in hydraulic, pneumatic, and fluidic design. The latter part focuses on electric and electronic controls, ending with robotics, robotic programming, and their industrial applications. Understanding these concepts is crucial for anyone looking to work in automation, as they provide the foundation for designing and maintaining automated systems. The course covers everything from basic laws and principles to advanced topics like the use of UAVs and AI in industrial automation.Throughout the course, you'll explore real-world applications and see how these principles are applied in industry. This structured approach ensures you gain a comprehensive understanding, from fundamental concepts to advanced automation and robotics techniques, preparing you for a career in this dynamic field.

Discrete Mathematics With Cryptographic Applications. A Self-Teaching Guide to Unlocking the Power of Advanced Concepts and Computational Techniques

Mercury Learning and Information, Alexander I. Kheyfits

This book offers a comprehensive guide to discrete mathematics and its applications to cryptography. It is designed for students and professionals in fields such as discrete mathematics and finite mathematics, with all necessary prerequisites clearly explained and illustrated. The text introduces key concepts in number theory, coding theory, and information theory, which are essential for understanding cryptography.Understanding discrete mathematics is crucial for anyone working in cryptography and related fields. The book begins with a survey of elementary functions and moves on to propositional algebra, set theory, and algebraic structures like groups, rings, and fields. It covers binary relations, combinatorics, and elements of number theory, which are fundamental to cryptographic methods.Readers will explore topics such as Boolean functions, hashing functions, cryptographic maps, combinatorial circuits, and graph theory. The book also delves into advanced areas like finite automata, game theory, and Turing machines. Through numerous examples, problems, and solutions, readers will gain a solid foundation in discrete mathematics and its cryptographic applications.

Python Tools for Data Scientists Pocket Primer. A Quick Guide to Essential Python Libraries for Data Science

Mercury Learning and Information, Oswald Campesato

This book, part of the best-selling Pocket Primer series, offers a comprehensive introduction to essential Python tools for data scientists. It begins with an overview of Python basics, followed by in-depth coverage of NumPy and Pandas, focusing on their features and applications. The text also addresses the critical tasks of writing regular expressions and performing data cleaning.Further sections delve into data visualization techniques and the use of Sklearn and SciPy, providing practical knowledge and skills for handling complex data analysis tasks. This structured approach ensures that readers gain a complete understanding of the tools and techniques necessary for effective data science.Designed to be accessible yet thorough, this book includes numerous code samples to reinforce learning. Companion files with source code are available for download, making it an invaluable resource for anyone looking to master Python for data science and enhance their data analysis capabilities.

Python Data Structures Pocket Primer. A concise guide to Python data structures to enhance your skills

Mercury Learning and Information, Oswald Campesato

This Pocket Primer book introduces the fundamentals of data structures using Python. It provides a comprehensive yet fast-paced introduction to core Python concepts and data structures, emphasizing their importance in managing large datasets and implementing search and sort algorithms effectively. The course starts with a basic introduction to Python, setting a solid foundation for more complex topics.The journey continues with an exploration of recursion and combinatorics, followed by detailed discussions on strings, arrays, and various search and sort algorithms. Further, the book delves into linked lists, queues, and stacks, illustrating their practical applications with numerous code samples. This structured approach ensures that learners can progressively build their knowledge and skills in data structures, reinforced by hands-on coding examples.With companion files available for download, the book provides additional resources for practice and deeper understanding. This comprehensive guide is ideal for both beginners and those looking to strengthen their grasp of data structures in Python, equipping them with essential tools for managing and manipulating large datasets.