Learn Dsa Using C Course in Sector39 Near Unitech Cyber Park Gurugram

Looking for professional Learn DSA in C & training in Gurugram Our comprehensive course at Blazingminds Learning is designed for students, working professionals, and business owners who want to gain practical expertise in C programming, Algorithms, Memory handling. The training covers industry-relevant concepts, hands-on projects, real-world case studies, and certification preparation to help learners build job-ready skills.

With expert trainers, flexible learning schedules, and placement assistance, our Learn DSA in C course in Gurugram helps participants stay competitive in today's job market. Whether you are a beginner or an experienced professional looking to upskill, this program provides the knowledge and practical experience needed to succeed.

Enroll today in the leading Learn DSA in C training institute in Gurugram and take the next step toward your career goals.

Industry Recognized Course

What You'll Learn

Learn core programming concepts

Memory management

Course Curriculum

5 Modules • 79 Lessons

Introduction to Data Structures

20 min Preview

Define the baseline purpose of data structures and identify how memory configurations alter program execution.

Need and Applications of Data Structures

10 min

Analyze operational bottlenecks in large software systems and map them to appropriate data structural solutions.

Types of Data Structures

20 min

Classify diverse data arrangement models into proper technical families based on how they layout data.

Primitive

20 min

Define how a computer's CPU allocates fixed byte widths to hold basic atomic data values natively.

Non-Primitive

10 min

Author complex object collections that integrate multiple primitive data types into singular entities.

Linear

10 min

Traversal linear memory arrangements sequentially using loop index counters or tracking reference pointers.

Non-Linear

10 min

Model complex, non-sequential data relationships where an element connects to multiple adjacent nodes.

Abstract Data Types (ADT)

20 min

Construct abstract software blueprints that define mathematical operations while hiding underlying data logic.

Time and Space Complexity

20 min

Calculate mathematical limits of software logic loops to measure operational runtime and memory efficiency.

Asymptotic Notations

20 min

Evaluate mathematical scale functions to express algorithmic processing limits under extreme volume stresses.

Big-O

20 min

Define the absolute mathematical ceiling of an algorithm's runtime to guarantee execution safety boundaries.

Big-Ω

20 min

Compute the structural lower bounds of programming logic blocks to map minimal execution requirements.

Big-Θ

20 min

Isolate tight mathematical bounds of an algorithm where best-case and worst-case execution lines merge.

Algorithm Analysis

15 min

Evaluate competing software algorithms using structural complexity checks to choose the fastest production tool.

Recursion and Recursive Algorithms

15 min

Code stable recursive execution steps paired with clear baseline conditions to prevent system memory stack drops.

Arrays

20 min Preview

Manage sequential, uniform data blocks in memory while executing real-time data insertions, reads, and deletions.

One-Dimensional Arrays

10 min

Construct indexing workflows to dynamically loop, search, and swap elements stored inside a single linear block.

Two-Dimensional Arrays

10 min

Map coordinate row/column indexing arrays to handle advanced spatial datasets and tabular matrix structures.

Sparse Matrices

15 min

Design custom array compression algorithms that store only meaningful non-zero values to reclaim system memory.

Linked Lists

20 min

Construct dynamic, non-contiguous data chains by allocating independent node data blocks connected via pointer paths.

Singly Linked List

20 min

Author structural pointer logic to insert, isolate, and prune data nodes across a one-way linear reference chain.

Doubly Linked List

20 min

Implement two-way pointer links within node structures to navigate collections both forward and backward seamlessly.

Circular Linked List

20 min

Construct an endless cyclical data ring by binding the tail boundary pointer directly back to the primary starting block.

Applications of Linked Lists

20 min

Deploy linked list node architectures to handle real-world software components like browser history tracks or dynamic caches.

Stack

15 min

Architect a classic LIFO stack pipeline to manage data items sequentially while strictly protecting entry/exit rules.

Array Implementation

10 min

Code a functional array-bound stack wrapper while writing explicit guard loops against structural overflow errors.

Linked List Implementation

10 min

Implement a dynamic, unconstrained heap stack utilizing node connection strings to bypass fixed hardware layout boundaries.

Applications of Stack

20 min

Build back-end validation utilities that evaluate balanced brackets or convert string formulas using stack engines.

Queue

20 min

Design an orderly FIFO data conduit to process incoming background tasks in the exact sequence they arrive.

Linear Queue

20 min

Author sequential enqueue and dequeue routines while diagnosing and resolving the data-drift capacity waste of linear lines.

Circular Queue

20 min

Implement a ring-buffer queue using boundary wrapping logic to reuse empty array index spaces automatically.

Priority Queue

20 min

Design a custom priority data pipeline that evaluates element labels to dynamically sort items into correct execution rankings.

Double-Ended Queue (Deque)

20 min

Code a bidirectional deque interface that handles independent push/pop operations at both the entry and exit boundaries.

Applications of Queues

20 min

Deploy queue data systems to handle asynchronous streaming tasks across network interfaces and server hardware layers.

Introduction to Trees

20 min Preview

Map complex multi-level file directories and organizational taxonomies into clean branching node structures.

Terminology and Properties

20 min

Calculate structural metrics of branching systems including depth boundaries, height levels, and leaf nodes.

Binary Trees

20 min

Construct a multi-tier branching node map where every node structure encapsulates data alongside a left and right reference pointer.

Binary Tree Traversals

20 min

Implement recursive tree-walking code loops to visit and display all node properties across a tree matrix cleanly.

Preorder

20 min

Code a preorder search routine to visit parent data blocks first before descending into left and right sub-branches sequentially.

Inorder

10 min

Author an inorder traversal algorithm that flattens multi-level search trees into clean, alphabetized data tables.

Postorder

10 min

Implement a postorder calculation loop to evaluate mathematical expression trees or safely dismantle hierarchical directories.

Binary Search Trees (BST)

20 min

Build a functional binary search tree that organizes incoming data values automatically for high-speed lookups.

AVL Trees

20 min

Design a self-adjusting AVL tree algorithm that uses dynamic node transformations to keep sub-branch heights uniformly balanced.

Heap Trees

20 min

Design an array-mapped binary heap layout while tracking complete binary structural rules.

Min Heap

20 min

Code a functional Min Heap structure that keeps the absolute smallest element at the root node for instant lookup.

Max Heap

20 min

Construct a Max Heap structure that isolates the absolute largest data item at the root interface.

Heap Operations

20 min

Implement $O(\log n)$ insertion, deletion, and structural heapify logic to repair broken heap properties dynamically.

Applications of Trees

20 min

Evaluate business data challenges to deploy tree models like trie routing maps or parsing systems.

Introduction to Graphs

20 min Preview

Map abstract, non-linear relational datasets into structured node-and-edge network graphs.

Graph Terminology

20 min

Compute basic network metrics including path lengths, node degrees, and connectivity loops across a graph system.

Graph Representations

10 min

Evaluate graph data structures to select the most efficient layout for dense versus sparse networks.

Adjacency Matrix

20 min

Construct an adjacency matrix layout that checks edge existences between vertices in instant $O(1)$ lookup times.

Adjacency List

20 min

Code a memory-efficient adjacency list wrapper that scales edge node allocations dynamically on the heap.

Graph Traversal

20 min

Implement graph-walking logic routines that visit every single vertex tracking path without getting stuck in network loops.

Breadth-First Search (BFS)

20 min

Author a functional BFS script to compute the shortest path across unweighted, network matrices.

Depth-First Search (DFS)

20 min

Code a recursive DFS engine to map path connectivity, detect routing cycles, and sort topological components.

Minimum Spanning Tree

20 min

Design optimization routines that isolate an MST from a weighted graph without building closed routing loops.

Prim's Algorithm

10 min

Code Prim's algorithm using minimum-edge priority arrays to grow a clean MST across a connected network matrix.

Kruskal's Algorithm

10 min

Implement Kruskal's algorithm paired with Disjoint-Set-Union (DSU) wrappers to build an MST without creating cycles.

Shortest Path Algorithms

20 min

Analyze complex network routing challenges to implement mathematical pathfinding algorithms.

Dijkstra's Algorithm

20 min

Construct a working Dijkstra pipeline that maps out the absolute fastest paths to all accessible network targets.

Applications of Graphs

10 min

Deploy network graph components to power practical business solutions like product recommendation engines or cluster maps.

Searching Techniques

20 min Preview

Evaluate array collection states to match your search logic smoothly with the underlying data order.

Linear Search

20 min

Author a linear search script that checks element indices sequentially while handling non-existent search targets gracefully.

Binary Search

20 min

Code a binary search engine using mid-point calculation splits to isolate values across sorted collections instantly.

Sorting Techniques

20 min

Analyze raw dataset parameters to select the safest, lowest-overhead sorting workflow for production systems.

Bubble Sort

20 min

Author nested bubble sort passes paired with early-termination optimization flags to sort simple array datasets.

Selection Sort

20 min

Construct a selection sort script that isolates minimal cell values to systematically organize target lists with minimal data moves.

Insertion Sort

20 min

Implement an insertion sort algorithm that shifts elements dynamically to sort live incoming record streams efficiently.

Merge Sort

20 min

Code a divide-and-conquer merge sort workflow that splits collections recursively before executing stable sorting merges.

Quick Sort

20 min

Implement an in-place quick sort framework utilizing optimized pivot partitioning strategies to organize arrays rapidly.

Heap Sort

20 min

Construct a heap sort pipeline that transforms a static data array into a Max Heap to sort variables in guaranteed $O(n \log n)$ time.

Comparison of Sorting Algorithms

20 min

Analyze structural data states to match them to the best sorting tool based on stability and memory restrictions.

Hashing Concepts

20 min

Articulate hashing design strategies to map large key spaces directly into compact, high-speed array slots.

Hash Functions

20 min

Construct balanced mathematical hashing expressions that distribute key strings evenly across an index array canvas.

Collision Resolution Techniques

20 min

Design fallback data systems that resolve index slot overlap errors smoothly without losing live records.

Chaining

20 min

Implement a separate chaining hash table that uses dynamic linked node strings to hold colliding database inputs safely.

Open Addressing

10 min

Author open-addressing routines that look up alternative array slots via custom probing increments during collision blocks.

Applications of Hashing

20 min

Deploy hashing systems to manage high-speed tracking arrays like compiler symbol dictionaries or fast lookup tables.

In case you are thinking of beginning your IT career, Learn DSA in C is the best course program to start and our Learn Dsa Using C Course in Sector39 Near Unitech Cyber Park Gurugram is structured in such a way that you will be job ready on the first day after course completion.

Course Description

Prerequisites

Basic Programming C Fundamentals

Skills You'll Gain

C Programming Algorithms Memory Handling

Your Instructors

Jyoti

Lead Instructor

AI Specialist

10+ Years Experience In C,C++ , AI Research, ML and Teaching Prestigious Universities. Total Expereince in teaching 12

⭐ 3.2 (139 Reviews)

👨‍🎓 1500 Students

📚 8 Courses

Student Reviews

4.8 (5 Rating or 4.8)

Manish Kumar

★ ★ ★ ★ ☆

"The best course to understand Data Structures and Algorithms using C. Every concept is explained with coding demonstrations, making complex topics easy to grasp."

Amit Sharma

★ ★ ★ ★ ★

"The practical approach to stacks, queues, linked lists, trees, and graphs made learning enjoyable. I now solve coding problems much more confidently."

Dipesh Pandey

★ ★ ★ ★ ☆

"A highly recommended course for interview preparation. The explanations are detailed, and the coding exercises strengthen problem-solving skills step by step."

Fateh Singh

★ ★ ★ ★ ☆

"Excellent teaching style with real-world examples and algorithm analysis. This course improved both my programming logic and coding efficiency. Great investment for aspiring developers."

Niharika Singh

★ ★ ★ ★ ☆

"Comprehensive DSA course with clear explanations, coding practice, and interview-focused problems. If you want to build strong programming fundamentals and crack technical interviews, enroll today—you won't regret it!"

FAQ

🔹 Is this course available online or offline?

Yes, course is available in both modes.

🔹 Certificate of completion?

Yes, shareable digital certificate.

🔹 Can i make fee payments in parts ?

Yes, Few basis , we allow candidates to pay fee in parts.

🔹 Projects included?

5 major minor portfolio projects.

🔹 Can you provide guaranteed placement after the course ?

Yes, we provide you the assured placement. we have a dedicated team for placement assistance.

Career Outcomes

Career outcomes will be added soon.

₹500 *Off on one-time payment

✨ 5-day money-back guarantee

Includes free 2-day preview session

Personalized Learning Roadmap
AI-Powered Learning Assistant
Hands-on Projects
Job-Ready Skills
Verified Certificate
24/7 Q&A/ Project Support

Course Features

17 Hrs.+ Sessions

15+ Exercises

Resources Kit

Daily Quiz-Assignments

Earn a Verified Certificate

Shareable on LinkedIn & Resume

Industry Recognized Verified by BMLC

❤️ We Care & Build Your Confidence

1-on-1 Mentorship: Dedicated professional mentors guide you through every challenge.

Peer Learning Community: Join 1k+ learners in weekly code reviews.

Confidence Booster: Project-based learning with real-world simulations.

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Upcoming Course Events

Live & Interactive-Offline

Oct

Coding session

Agentic AI Session

Praveen Y

01:00 PM - 01:00 PM

Build Agents Quickly

45 attending

*All events are recorded and available for enrolled students

Learn Dsa In C