NSCT Syllabus 2026

Syllabus 2026 

Areas of Competencies for National Skill Competency Test of IT Graduates
Areas of Competencies Weightage

Computer Networks and Cloud Computing

10%

Programming (C++/Java/Python)

10%

Data Structures & Algorithms

10%

Operating Systems

5%

Software Engineering

10%

Web Development

10%

AI / Machine Learning and Data Analytics

10%

Cyber Security

5%

Databases

10%

Problem Solving and Analytical Skills

20%

NSCT IT Graduates Syllabus 2026 (Table Form)
Areas of Competencies Weightage % Topics

Computer Networks and Cloud Computing

10%

1 – Data Communication

2 – Computer Networks

3 – Data Link Layer

4 – Network Layer

5 – Transport Layer

6 – Application Layer

7 – Wireless Networks

8 – Cloud Computing

9 – Network Security (Networks Perspective)

10 – Next Generation Networks

Programming (C++/Java/Python)

10%

1 – Programming Fundamentals

2 – Data Types & Variables

3 – Operators & Expressions

4 – Control Structures

5 – Functions / Methods

6 – Input / Output Handling

7 – Strings & Text Processing

8 – Arrays & Collections

9 – OOP

10 – Memory Management Concepts

11 – Exception & Error Handling

12 – Modules, Packages & Libraries

13 – Advanced Programming Concepts

14 – Concurrency & Parallelism (Introductory)

15 – Debugging, Testing & Optimization

16 – Software Development Practices

Data Structures & Algorithms

10%

1 – Foundations of Data Structures & Algorithms

2 – Linear Data Structures

3 – Non-Linear Data Structures

4 – Searching Algorithms

5 – Sorting Algorithms

6 – Hashing

7 – Tree Algorithms

8 – Graph Algorithms

9 – Algorithm Design Techniques

10 – Advanced Data Structures

11 – String Algorithms

12 – Complexity & Optimization

Operating Systems

5%

1 – Introduction to Operating Systems

2 – OS Structures

3 – Process Management

4 – CPU Scheduling

5 – Thread Management

6 – Concurrency & Synchronization

7 – Deadlocks

8 – Memory Management

9 – File System Management

10 – Secondary Storage Management

11 – I/O Systems

12 – Protection & Security

Software Engineering

10%

1 – Introduction to Software Engineering

2 – Software Process Models

3 – Agile Development

4 – Requirements Engineering

5 – Project Management

6 – Software Design

7 – Software Architecture

8 – UI Design

9 – Implementation & Coding

10 – Software Testing

11 – Maintenance & Evolution

12 – Quality Assurance

13 – Metrics

14 – Configuration Management

15 – Risk Management

16 – Software Security Engineering

Web Development

10%

1 – Introduction to Web Development

2 – Web Architecture & Protocols

3 – HTML Fundamentals

4 – CSS Fundamentals

5 – Responsive Design

6 – JavaScript Fundamentals

7 – Advanced JavaScript

8 – Frontend Frameworks

9 – Backend Development

10 – Server-Side Programming

11 – Web Databases

12 – Web Security

13 – Performance Optimization

14 – Testing & Debugging

15 – Deployment & Hosting

16 – Web APIs

17 – Modern Web Practices

AI / ML & Data Analytics

10%

1 – Introduction to AI/ML

2 – Mathematical Foundations

3 – Python for AI

4 – Data Pre-processing

5 – EDA

6 – Supervised Learning

7 – Ensemble Learning

8 – Unsupervised Learning

9 – Model Evaluation

10 – Feature Engineering

11 – Deep Learning Basics

12 – Advanced Deep Learning

13 – NLP

14 – Computer Vision

15 – Big Data Intro

16 – MLOps Basics

17 – AI Ethics

Cyber Security

5%

1 – Introduction to Cyber Security

2 – Security Principles

3 – Cryptography Basics

4 – Network Security

5 – OS Security

6 – Web Security

7 – Malware & Attacks

8 – Authentication

9 – Secure Development

10 – Wireless Security

11 – Cloud Security

12 – Digital Forensics

13 – Incident Response

14 – Monitoring

15 – Cyber Laws

16 – Trends

Databases

10%

1 – Introduction to DBMS

2 – Database Architecture

3 – Data Models

4 – Relational Concepts

5 – Relational Algebra

6 – SQL

7 – Advanced SQL

8 – Normalization

9 – Transactions

10 – Concurrency Control

11 – Recovery Management

12 – Indexing

13 – Query Optimization

14 – Security

15 – Distributed Databases

16 – NoSQL

17 – Data Warehousing

Problem Solving & Analytical Skills

20%

1 – Problem Understanding

2 – Analysis

3 – Logical Reasoning

4 – Algorithms & Flow Control

5 – Data Representation

6 – Pattern Recognition

7 – Mathematical Reasoning

8 – Algorithmic Thinking

9 – Critical Thinking

10 – Debugging

11 – Efficiency Awareness

12 – Programming Problem Solving

13 – Data-driven Thinking

14 – Creativity

15 – Real-world Problems

16 – Communication Skills

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