Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, ...

Learning Outcomes Explain fundamental concepts for algorithmic searching and sorting Describe heap data structures and analyze heap components, such as arrays and priority queues Design basic ...

Description The design, implementation, and analysis of abstract data types, data structures and their algorithms. Topics include: data and procedural abstraction, amortized data structures, trees and ...

Depending on the data structures and processes involved in an application, it may become necessary to sort the data stored within it. Different data structures enforce certain constraints on ...

Once you’ve got these basics, you’ll be ready to learn about searching and sorting with one-dimensional arrays, in Part 2. What is a data structure?

An introduction to the analysis and implementation of algorithms and data structures including linear data structures, trees, graphs, hash tables, searching algorithms, sorting algorithms, ...

Development of more sophisticated ideas in data type and structure, with an introduction to the connection between data structures and the algorithms they support. Data abstraction. Controlled access ...