Data Structure Using C

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Data Structure Using C

COURSE OVERVIEW

The Data Structure Using C course develops a structured foundation across four source-defined units. Learners begin with foundations of data structures, algorithms, adts, and complexity, growth rates, asymptotic thinking, space complexity, and better choices, progress to linear data structures, arrays, and memory layout, linked lists, stacks, queues, then move into trees, binary search trees, and close with graphs, hashing, sorting. The sequence is supported by theory sessions, course materials, code practice and practice codes, helping learners connect each unit with a consistent learning rhythm.

The source curriculum connects these ideas through ADTs and complexity, linear structures, trees, graphs, hashing and sorting, supported by repeated code practice. Designed for students, technical learners and early-career professionals, the course provides a focused six-week online pathway that preserves the supplied module order and topic pattern. The emphasis remains on the skills and concepts named in the source curriculum, with no unsupported modules, tools or outcomes added.

WHAT YOU'LL LEARN

Explain data-structure, algorithm and abstract-data-type foundations.
Interpret growth rates, asymptotic thinking and space complexity.
Work with arrays and memory-layout concepts.
Develop understanding of linked lists, stacks and queues.
Explain tree structures and binary search trees.
Describe graph representations and related problem structures.
Develop understanding of hashing and sorting approaches.
Connect theory and complexity choices with C-based code practice.

Strengthen algorithmic thinking with core data structures implemented in C

CURRICULUM

Unit 1: Foundations of Data Structures, Algorithms, ADTs, and Complexity, Growth Rates, Asymptotic Thinking, Space Complexity, and Better Choices

Topics Covered:

This opening module establishes foundations of data structures, algorithms, adts, and complexity, growth rates, asymptotic thinking, space complexity, and better choices within the Data Structure Using C learning pathway. Theory sessions and course materials establish the concepts, while code practice and practice codes reinforce them through repeated programming activity. It creates the foundation for the later modules without adding topics beyond the supplied curriculum.

Theory Sessions
Course Materials
Code Practice
Practice Codes

Unit 2: Linear Data Structures, Arrays, and Memory Layout, Linked Lists, Stacks, Queues

Topics Covered

This module develops linear data structures, arrays, and memory layout, linked lists, stacks, queues as the next stage of the Data Structure Using C pathway. Theory sessions and course materials establish the concepts, while code practice and practice codes reinforce them through repeated programming activity. The unit connects the earlier foundation with the concepts introduced in the modules that follow.

Theory Sessions
Course Materials
Code Practice
Practice Codes

Unit 3: Trees, Binary Search Trees

Topics Covered

This module develops trees, binary search trees as the next stage of the Data Structure Using C pathway. Theory sessions and course materials establish the concepts, while code practice and practice codes reinforce them through repeated programming activity. The unit connects the earlier foundation with the concepts introduced in the modules that follow.

Theory Sessions
Course Materials
Code Practice
Practice Codes

Unit 4: Graphs, Hashing, Sorting

Topics Covered

The final module focuses on graphs, hashing, sorting, completing the source-defined Data Structure Using C sequence. Theory sessions and course materials establish the concepts, while code practice and practice codes reinforce them through repeated programming activity. It brings the four-module pathway to a clear conclusion while preserving the exact source topic structure.

Theory Sessions
Course Materials
Code Practice
Practice Codes

WHO SHOULD ENROLL

Students building a foundation in data structures and algorithms using C.
C learners ready to move beyond basic syntax into structured problem solving.
Early-career developers refreshing core data-structure concepts.
Technical learners preparing for algorithm-focused coursework or interviews.
Programmers who want stronger understanding of complexity and implementation choices.
Learners comfortable with theory, course materials and regular code practice.