Mastering AngularJS for .NET Developers

More Information
Learn
  • Understand the architecture of AngularJS
  • Discover the uses and working of data binding in AngularJS
  • Learn the scope of AngularJS with a thorough understanding of the controller and the filter
  • Master the use of $http and $resources to communicate with the server in order to retrieve and post data
  • Integrate an AngularJS application with Entity Framework and ASP.NET Web API 2 while learning about the use of JSON objects in AngularJS
  • Walk through the development environment using the AngularJS NuGet packages
  • Learn about troubleshooting and debugging options in an AngularJS application by using different libraries and tools
  • Discover the uses of Visual Studio 2013 to build CRUD operations using ASP.NET Web API 2 and AngularJS
  • Authenticate and understand security mechanisms for AngularJS applications
About

AngularJS is an open source framework that utilizes the Model-View-Controller architecture for client-side application development. AngularJS is referred to as the Angular framework.

With this book, you will soon be able to build client-side data driven applications. The introduction section covers the essentials of AngularJS, covering the core concepts of AngularJS to ensure a smooth transition to the more advanced topics discussed later on.

This book covers the development of client-side applications with AngularJS using code examples before moving on to explore how to build the ASP.NET Web API and its features using Visual Studio .NET.

Features
  • Learn how to utilize the robust features of the AngularJS framework
  • Explore the opportunity to develop client-side applications for cross-platforms such as web and mobile
  • Step-by-step guide with detailed instructions on how to develop and use the ASP.Net Web API with AngularJS
Page Count 214
Course Length 6 hours 25 minutes
ISBN 9781783553983
Date Of Publication 29 Apr 2015

Authors

Mohammad Wadood Majid

Mohammad Wadood Majid has been working in the field of application development and design for more than a decade for some major companies in the USA. During this time, he has worked independently as well as with teams to develop a number of highly successful enterprise applications for the Web and mobiles. He is experienced in the development, designing, testing, modification, and maintenance of enterprise applications. Currently, he is working as an enterprise application administrator and developer and a part-time assistant professor at the University of Toledo.

He has worked extensively with MVC, web APIs, ASP.NET, ADO.NET, C#, OData, and RESTful. He has expertise in native mobile apps and web-based application development that can be performed using HTML5, JavaScript, jQuery, Bootstrap, AngularJS, and CSS.

He has experience of working with databases such as SQL Server 2012 and Oracle 11g.

He has also performed research on the following topics:

  • Parallel implementation of algorithms on multicore and NVIDIA's GPU
  • Parallel computation of moving target detection and recognition from a set of radar signals
  • Development of parallel programs using multicore and NVIDIA's GPU for artificial intelligent algorithms, such as evolutionary neural networks and genetic algorithms

Golrokh Mirzaei

Golrokh Mirzaei has several years of software development experience in the software industry and is currently working as a faculty at the Ohio State University. Her research involves the development of software applications and multisensor data fusion approach to monitor biological targets using three different sensors: infrared camera (IR), radar, and acoustics. The infrared camera and radar sensors involve video and image processing techniques, including object detection and recognition, feature extraction, classification/clustering, and tracking. She has published several papers at professional IEEE conferences and received several awards. Her developments in the field of image processing and computer vision are unique, related to multifidelity, and multidisciplinary.

She has also performed research on the following topics:

  • Pattern recognition (object detection, feature extraction, tracking, and so on)
  • Machine learning (supervised/unsupervised learning)
  • Classification/clustering
  • Image/video/audio processing (infrared camera, radar, and acoustics)
  • Bio-inspired computing (ACA, ACO, and GA)
  • Bayesian inference and fuzzy reasoning