Data Structure and Algorithms (C, C++, Java, Python)
Build a strong foundation in Data Structures and Algorithms across C, C++, Java and Python. Explore arrays, searching, sorting, linked lists, stacks, queues, trees, graphs, hashing, heaps and algorithm analysis through a structured training program.
Learn Data Structures and Algorithms at NIPSTec
The Data Structure and Algorithms course at NIPSTec introduces learners to core data structures, algorithm design, problem-solving techniques, and complexity analysis using C, C++, Java and Python.
The 2-month, 40+ hour offline program covers arrays, searching and sorting, linked lists, stacks, queues, trees, graphs, hashing, heaps, and graph algorithms.
Training methodology includes pre-training assessment, expert-led classes, and post-training evaluation.
Data Structures & Algorithms Course Highlights
DSA Fundamentals
Understand algorithms, data structure types, abstract data types, and static versus dynamic structures.
Arrays, Searching & Sorting
Practice array operations, linear and binary search, and common sorting algorithms.
Linked Lists, Stacks & Queues
Explore linked-list variations, stack operations, queue types, deques, and their implementations.
Trees, Graphs & Traversals
Learn binary trees, BST, AVL trees, graph representations, BFS, DFS, and graph algorithms.
Complexity Analysis
Study Big-O, Big-Ξ© and Big-Ξ notation with best-, average-, and worst-case analysis.
Hashing & Heaps
Cover hash tables, collision handling, heap operations, heapify, and priority queues.
Data Structures & Algorithms Course Overview
This program builds algorithmic problem-solving skills through core data structures, searching and sorting methods, complexity analysis, and graph-based techniques.
Data Structures & Algorithms Course Curriculum
Curriculum topics are adapted from the supplied DSA course brochure.
Module 1Introduction to DSAβ
- Introduction to data structures
- What is an algorithm?
- Characteristics of an algorithm
- Types of data structures
- Linear and non-linear data structures
- Static vs. dynamic data structures
- Abstract Data Type (ADT)
Module 2Arrays & Array Operationsβ
- One-dimensional, two-dimensional and multidimensional arrays
- Array traversal, insertion, deletion, searching and updating
- Finding largest, smallest, second largest and second smallest elements
- Kth largest and Kth smallest elements
Module 3Searching, Sorting & Complexityβ
- Linear, binary and interpolation search
- Bubble, selection and insertion sort
- Merge sort and quick sort
- Heap, counting, radix and bucket sort
- Time complexity
- Big-O, Big-Ξ© and Big-Ξ notation
- Best, average and worst case analysis
Module 4Linked Listsβ
- Singly linked list
- Doubly linked list
- Circular linked list
- Circular doubly linked list
Module 5Stacks, Queues & Dequesβ
- Stack and LIFO concept
- Stack using array and linked list
- Push, pop, peek/top, display, overflow and underflow
- Queue and FIFO concept
- Queue using array and linked list
- Enqueue, dequeue, peek and display
- Simple, circular and priority queues
- Deque, input-restricted and output-restricted deque
Module 6Trees & Heapsβ
- Binary tree
- Binary Search Tree (BST)
- AVL tree
- Introduction to heaps, min heap and max heap
- Heap representation using array
- Insertion, deletion, heapify and build heap
- Heap sort
- Priority queue using heap
Module 7Graphs & Graph Algorithmsβ
- Graph terminology: vertex, edge and degree
- Directed, undirected, weighted and unweighted graphs
- Adjacency matrix and adjacency list
- Graph traversal: BFS and DFS
- Dijkstra's algorithm
- Prim's algorithm
- Kruskal's algorithm
- FloydβWarshall algorithm
Module 8Hashingβ
- Introduction to hashing and hash tables
- Hash functions and collisions
- Division/modulo, mid-square, folding and multiplication methods
- Collision resolution
- Chaining, linear probing, quadratic probing and double hashing
Languages & Concepts You'll Learn
The brochure identifies these programming languages and DSA topics:
Career Areas Related to DSA Training
Data structures and algorithms are commonly used in software development and technical problem-solving. Role requirements vary by employer and experience.
Software Developer
Apply programming fundamentals and data structures to software tasks.
Programmer
Implement algorithms and solve coding problems.
Software Development Trainee
Build foundational coding and problem-solving skills.
Application Developer
Use data structures in application logic and features.
Technical Interview Preparation
Practice common algorithmic concepts used in assessments.
Competitive Programming Learner
Develop a base for structured coding challenges.
Learning & Practical Support
Structured Learning
Progress from foundational concepts to advanced structures and algorithms.
Offline Classroom Training
Attend the 2-month, 40+ hour program in offline mode.
Pre-Training Assessment
Assess current skills and learning needs before training.
Expert-Led Classes
Learn with qualified and experienced trainers.
Post-Training Evaluation
Review progress after completing the course.
Why Choose NIPSTec
NIPSTec's brochure highlights 25+ years of training experience, PAN India reach, training for corporates, PSUs, government and private-sector learners, an ISO 9001:2015 certified company, qualified and experienced trainers, job-oriented programs, and industry-relevant curriculum.
25+ Years of Experience
Training students and corporates.
PAN India Reach
Training reach across India.
Industry-Relevant Curriculum
Course topics outlined in the brochure.
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Data Structures & Algorithms FAQs
What is the duration of the course?
The brochure specifies 2 months and 40+ hours.
Which programming languages are covered?
The course is presented for C, C++, Java and Python.
What topics are included?
Topics include arrays, searching, sorting, linked lists, stacks, queues, trees, graphs, hashing, heaps, and algorithm analysis.