Course Description
This course provides a strong foundation in data structures and algorithms, which are essential for writing efficient and effective software applications. The course equips participants with the skills needed to solve complex problems and optimize algorithms for various applications. Data structures are essential for efficiently organizing and manipulating data, and proficiency in this area is crucial for programming, software engineering, and computer science careers.
Prerequisites: Basic programming knowledge, preferably in a language like C++, Java, or Python, is recommended. Familiarity with fundamental computer science concepts is advantageous.
Introduction to Data
Structures:
An overview
of data structures and their significance in computer science and software
development.
The role of
data structures in efficient data organization and retrieval.
Array and Linked List:
In-depth
coverage of arrays and linked lists as fundamental data structures.
Understanding
their implementation, traversal, and operations.
Stacks and Queues:
Comprehensive
exploration of stacks and queues as linear data structures.
Their
applications in managing data and algorithms.
Trees and Binary Trees:
Introduction
to trees and binary trees as hierarchical data structures.
Understanding
tree traversal, searching, and balancing.
Graphs and Graph Algorithms:
The concept
of graphs as non-linear data structures.
Learning
graph algorithms, such as breadth-first search (BFS) and depth-first search
(DFS).
Sorting and Searching Algorithms:
In-depth
study of sorting algorithms like quicksort, mergesort, and selection sort.
Introduction
to searching algorithms, including binary search and linear search.
Hashing and Hash Tables:
Understanding
hashing and hash table data structures.
Exploring
collision resolution techniques and applications.
Complexity Analysis:
Analysing
time and space complexity of data structures and algorithms.
Big O
notation and its significance in algorithm performance.
Dynamic Programming:
Introduction
to dynamic programming as a problem-solving technique.
Applying
dynamic programming to optimize algorithms.
Advanced Data Structures:
Exploring
advanced data structures like heaps, graphs, and self-balancing trees.
Their
applications in real-world scenarios.
Real-World Applications:
Hands-on
projects and practical assignments simulating real-world data structure
applications.
Solving
problems using the knowledge gained in the course.
Certification: Upon successful completion
of the course, participants will receive a certificate showcasing their
proficiency in data structures.