Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis ...

In practice, exploratory data analysis combines graphics and descriptive statistics. In a highly cited book chapter, Tukey uses R to explore the 1990s Vietnamese economy with histograms, kernel ...

“That’s why it’s difficult to perform the analysis without designing the data structures purposefully. It’s difficult to back annotate measurements after the fact.” Data structures and computing Once ...

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 search ...

We look at how to gain structure from unstructured data, via AI/ML analytics to create new records, selecting object data via SQL and storing unstructured files in NoSQL formats.

Covers algorithms and their performance analysis, data structures, abstraction, and encapsulation. Introduces stacks, queues, linked lists, trees, heaps, priority queues, and hash tables, and their ...

Specialization: Foundations of Data Structures and Algorithms; Instructor: Dr. Sriram Sankaranarayanan, Professor of Computer Science; Prior knowledge needed: You must understand all concepts covered ...