Understand basic data structures like arrays, linked lists, trees, and graphs. Learn how to sort and search data efficiently. Analyze the performance of algorithms using time complexity.

It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.

Mar 4, 2024 · During this period, you will learn core C programming along with Data Structures and Algorithms. We offer hands-on training after the completion of each module so that you can implement your theoretical knowledge into real-life data structure projects .

Description: Intensive study of the fundamentals of data structures and algorithms. Presents the defini-tions, representations, processing algorithms for data structures, general design and analysis techniques for algorithms. Covers a broad variety of data structures, algorithms and their

Teaching assistants: Gary Yngve and Tobias Roseman. Overview and Goals: Achieve an understanding of fundamental data structures and algorithms and the tradeoffs between different implementations of these abstractions. Theoretical analysis, implementation, and application.

Analyze searching and sorting algorithms, and explain their relationship to data-structures. Choose and implement appropriate data-structures to solve an application problem. Understand techniques of software development, such as unit testing and version control.

Fundamentals of programming and OOP design: proving program correctness, evaluating program speed; testing, debugging, and control flow. Fundamental data structures: linked lists, queues, stacks, trees, heaps, maps, hash tables. Sorting and search algorithms: selection, heap, quick, merge sort; linear, binary, tree-based, hash-based search.

Introduction to the intellectual enterprises of computer science and the art of programming. This course teaches students how to think algorithmically and solve problems efficiently. Topics include abstraction, algorithms, data structures, encapsulation, resource management, security, and software engineering. Languages include C, Python, and SQL plus HTML, CSS, and JavaScript. Problem sets ...

This document provides information about a Data Structures and Algorithms course offered at Cavite State University, including: 1. The course description, prerequisites, schedule, and core values of the university. 2. The goals and objectives of the college, campus, and department relating to providing globally competitive education. 3.

Topics include stacks, queues, lists, trees, graphs, sorting, searching, and hashing. The course introduces abstract data types, dynamic memory allocation, asymptotic analysis, and common algorithms like recursion, binary search trees, and shortest path algorithms.