- Promoted by: Anonymous
- Platform: Udemy
- Category: Engineering
- Language: English
- Instructor: Lendale Venkateswarlu
- Duration: 2 hour(s) 35 minute(s)
- Student(s): 933
- Rate 0 Of 5 From 0 Votes
- Expires on: 2026/01/03
-
Price:
19.990
Arrays & Linked Lists, Stacks, Queus, Trees • Graphs • Searching
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for the "Fundamentals of Data Structures: An Algorithmic Approach" course by Lendale Venkateswarlu on Udemy.
This course, boasting a 0.0-star rating from 0 reviews
and with 933 enrolled students, provides comprehensive training in Engineering.
Spanning approximately
2 hour(s)
35 minute(s)
, this course is delivered in English
and we updated the information on December 31, 2025.
To get your free access, find the coupon code at the end of this article. Happy learning!
Fundamentals of Data Structures: An Algorithmic Approach offers engineering students a comprehensive understanding of how data can be efficiently organized, stored, and processed to solve computational problems. The course begins by introducing the importance of selecting appropriate data structures and the role they play in designing effective algorithms. Students explore a wide range of linear and non-linear structures, including arrays, linked lists, stacks, queues, trees, heaps, and graphs. Each structure is examined in terms of its properties, operations, applications, and performance characteristics.
A major focus of the course is helping students understand how algorithms interact with these data structures. Through detailed explanations, visual demonstrations, and animated representations, students learn to trace the flow of algorithms such as searching, sorting, traversing, and manipulating data. Special emphasis is placed on analyzing time and space complexity using asymptotic notation, enabling learners to evaluate the efficiency of different algorithmic approaches.
The course is particularly supportive for students who may find coding difficult or struggle to visualize algorithmic steps. By using animations and simplified representations, the course builds intuition and confidence in algorithmic thinking. As students progress, they gradually develop strong problem-solving abilities and the capability to choose the most suitable data structure for a given task.
By the end of the course, learners are well-prepared to design robust data-handling mechanisms, optimize computational processes, and apply algorithmic reasoning to a variety of real-world engineering challenges. This foundational knowledge serves as a stepping stone for more advanced subjects in computer science and software development.