Moodle Course Design Best Practices. Design and develop outstanding Moodle learning experiences - Second Edition

Susan Smith Nash

Moodle is a leading virtual learning environment for your online course. This book incorporates the principles of instructional design, showing you how to apply them to your Moodle courses. With this guidance, you will develop and deploy better courses, content, and assessments than ever.This book will guide you as you learn how to build and incorporate many different types of course materials and dynamic activities. You will learn how to improve the structure and presentation of resources, activities, and assessments. All this will help you to create better for self-led courses, instructor-led courses, and courses for collaborative groups. The use of multimedia features to enhance your Moodle courses is also explained in this book.Our goal is to encourage creativity, and the free MoodleCloud hosting option is an ideal place for teachers, students, trainers, and administrators to jump in and play with all the new features, which include powerful new plug-ins, new resources, and activities.Moodle can be your sandbox as well as your castle of learning! With this book, you will build learning experiences that will last your learners’ lifetimes.

GitHub Essentials. Unleash the power of collaborative development workflows using GitHub - Second Edition

Achilleas Pipinellis

Whether you are an experienced developer or a novice, learning to work with Version Control Systems is a must in the software development world. Git is the most popular tool for that purpose, and GitHub was built around it, leveraging its powers by bringing it to the web.Starting with the basics of creating a repository, you will then learn how to manage the issue tracker, the place where discussions about your project take place. Continuing our journey, we will explore how to use the wiki and write rich documentation that will accompany your project. You will also master organization/team management and some of the features that made GitHub so well known, including pull requests. Next, we will focus on creating simple web pages hosted on GitHub and lastly, we will explore the settings that are configurable for a user and a repository.

Graph Machine Learning. Take graph data to the next level by applying machine learning techniques and algorithms

Claudio Stamile, Aldo Marzullo, Enrico Deusebio

Graph Machine Learning will introduce you to a set of tools used for processing network data and leveraging the power of the relation between entities that can be used for predictive, modeling, and analytics tasks. The first chapters will introduce you to graph theory and graph machine learning, as well as the scope of their potential use. You’ll then learn all you need to know about the main machine learning models for graph representation learning: their purpose, how they work, and how they can be implemented in a wide range of supervised and unsupervised learning applications. You'll build a complete machine learning pipeline, including data processing, model training, and prediction in order to exploit the full potential of graph data. After covering the basics, you’ll be taken through real-world scenarios such as extracting data from social networks, text analytics, and natural language processing (NLP) using graphs and financial transaction systems on graphs. You’ll also learn how to build and scale out data-driven applications for graph analytics to store, query, and process network information, and explore the latest trends on graphs. By the end of this machine learning book, you will have learned essential concepts of graph theory and all the algorithms and techniques used to build successful machine learning applications.

Moodle E-Learning Course Development. A complete guide to create and develop engaging e-learning courses with Moodle

William Rice, William Rice

Pentesting Industrial Control Systems. An ethical hacker's guide to analyzing, compromising, mitigating, and securing industrial processes

Paul Smith

The industrial cybersecurity domain has grown significantly in recent years. To completely secure critical infrastructure, red teams must be employed to continuously test and exploit the security integrity of a company's people, processes, and products.This is a unique pentesting book, which takes a different approach by helping you gain hands-on experience with equipment that you’ll come across in the field. This will enable you to understand how industrial equipment interacts and operates within an operational environment.You'll start by getting to grips with the basics of industrial processes, and then see how to create and break the process, along with gathering open-source intel to create a threat landscape for your potential customer. As you advance, you'll find out how to install and utilize offensive techniques used by professional hackers. Throughout the book, you'll explore industrial equipment, port and service discovery, pivoting, and much more, before finally launching attacks against systems in an industrial network.By the end of this penetration testing book, you'll not only understand how to analyze and navigate the intricacies of an industrial control system (ICS), but you'll also have developed essential offensive and defensive skills to proactively protect industrial networks from modern cyberattacks.

Data Wrangling with R. Load, explore, transform and visualize data for modeling with tidyverse libraries

Gustavo R Santos

In this information era, where large volumes of data are being generated every day, companies want to get a better grip on it to perform more efficiently than before. This is where skillful data analysts and data scientists come into play, wrangling and exploring data to generate valuable business insights. In order to do that, you’ll need plenty of tools that enable you to extract the most useful knowledge from data.Data Wrangling with R will help you to gain a deep understanding of ways to wrangle and prepare datasets for exploration, analysis, and modeling. This data book enables you to get your data ready for more optimized analyses, develop your first data model, and perform effective data visualization.The book begins by teaching you how to load and explore datasets. Then, you’ll get to grips with the modern concepts and tools of data wrangling. As data wrangling and visualization are intrinsically connected, you’ll go over best practices to plot data and extract insights from it. The chapters are designed in a way to help you learn all about modeling, as you will go through the construction of a data science project from end to end, and become familiar with the built-in RStudio, including an application built with Shiny dashboards.By the end of this book, you’ll have learned how to create your first data model and build an application with Shiny in R.

Apps and Services with .NET 7. Build practical projects with Blazor, .NET MAUI, gRPC, GraphQL, and other enterprise technologies

Mark J. Price

Apps and Services with .NET 7 is for .NET 6 and .NET 7 developers who want to kick their C# and .NET understanding up a gear by learning the practical skills and knowledge they need to build real-world applications and services. It covers specialized libraries that will help you monitor and improve performance, secure your data and applications, and internationalize your code and apps.With chapters that put a variety of technologies into practice, including Web API, OData, gRPC, GraphQL, SignalR, and Azure Functions, this book will give you a broader scope of knowledge than other books that often focus on only a handful of .NET technologies. It covers the latest developments, libraries, and technologies that will help keep you up to date.You’ll also leverage .NET MAUI to develop mobile apps for iOS and Android as well as desktop apps for Windows and macOS.

Python Data Cleaning and Preparation Best Practices. A practical guide to organizing and handling data from various sources and formats using Python

Maria Zervou

Professionals face several challenges in effectively leveraging data in today's data-driven world. One of the main challenges is the low quality of data products, often caused by inaccurate, incomplete, or inconsistent data. Another significant challenge is the lack of skills among data professionals to analyze unstructured data, leading to valuable insights being missed that are difficult or impossible to obtain from structured data alone.To help you tackle these challenges, this book will take you on a journey through the upstream data pipeline, which includes the ingestion of data from various sources, the validation and profiling of data for high-quality end tables, and writing data to different sinks. You’ll focus on structured data by performing essential tasks, such as cleaning and encoding datasets and handling missing values and outliers, before learning how to manipulate unstructured data with simple techniques. You’ll also be introduced to a variety of natural language processing techniques, from tokenization to vector models, as well as techniques to structure images, videos, and audio.By the end of this book, you’ll be proficient in data cleaning and preparation techniques for both structured and unstructured data.