Introduction to the fundamental principles of data structures and algorithms and their efficient implementation. Developing algorithmic thinking. Basic toolkit for the design and analysis of ...

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

Learn when and how to use different data structures and their algorithms in your own code. This is harder as a student, as the problem assignments you'll work through just won't impart this knowledge.

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 ...

Specialization: Data Science Foundations: Data Structures and Algorithms Instructor: Sriram Sankaranarayanan, Assistant Professor Prior knowledge needed: Mathematical Background: We expect that the ...

Cross-listed with DTSA 5503. Course Type: Pathway | Breadth Specialization: Foundations of Data Structures and Algorithms Instructor: Dr. Sriram Sankaranarayanan, Professor of Computer Science Prior ...

22:544:643 Information Security 22:544:603 Business Data Management 22:544:641 Analytics for Business Intelligence (or 22:544:650 Data Mining) 22:544:613 Introduction to Data Structures and Algorithms ...

Here, the authors propose a quantum machine learning algorithm that provides an exponential speed up over known algorithms for topological data analysis. Extracting useful information from large ...