Collections and Generics in C#
Working with multitudes of objects and using generics requires understanding of programming theory and textbook algorithms. This course will teach you effective use of .NET collections and power of generalization through generic classes and methods.
Processing many objects is usually tied with knowing non-trivial algorithms, as well as with meeting nonfunctional requirements, such as time and space considerations or deferred execution. In this course, Collections and Generics in C#, you’ll learn to consume and process many objects with optimal algorithms. First, you’ll explore algorithms on linear and associative collections, such as lists, arrays, dictionaries, etc. Next, you’ll discover how to generalize algorithms by applying advanced generics to your classes and methods. Finally, you’ll learn how to combine existing collections to build your own highly specialized collections that are applicable in business models. When you’re finished with this course, you’ll have the skills and knowledge of algorithms that apply to many objects, needed to develop highly optimized business applications.
Author Name: Zoran Horvat
Author Description:
Zoran Horvat is Principal consultant at Coding Helmet Consultancy, speaker and author of 100+ articles, and independent trainer on .NET technology stack. He can often be found speaking at conferences and user groups, promoting object-oriented development style and clean coding practices and techniques that improve longevity of complex business applications.
Table of Contents
- Course Overview
1min - Introducing Collections and Generics
26mins - Using Linear Collections: Lists and Arrays
33mins - Building on Ordered and Partially Ordered Lists
27mins - Measuring and Optimizing Performance
27mins - Using Generic Types in the Object Model
20mins - Designing Generic Types
19mins - Using Associative Collections
33mins - Engineering Solutions Using Associative Collections
31mins - Engineering Custom Linear Collections
29mins - Engineering Queuing Solutions
31mins
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