VU HEC NSCT Syllabus, Paper Pattern, sample paper, Past Papers 2026.
(Original
Paper Pattern 2026
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Approximately |
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Total Marks: |
100 |
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Total MCQs: |
100 |
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Total Time |
120 minutes |
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Test Medium |
MCQs on Computer |
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Negative Marking |
No |
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Paper Language |
English |
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Syllabus 2026 سلیبس
Areas of Competencies for National Skill Competency Test of IT
Graduates
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Areas of Competencies |
Weightage |
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Computer Networks and Cloud Computing |
10% |
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Programming (C++/Java/Python) |
10% |
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Data Structures & Algorithms |
10% |
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Operating Systems |
5% |
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Software Engineering |
10% |
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Web Development |
10% |
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AI / Machine Learning and Data Analytics |
10% |
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Cyber Security |
5% |
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Databases |
10% |
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Problem Solving And Analytical Skills |
20% |
سلیبس وضاحت کے ساتھ ٹاپکس وائز
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Areas of Competencies |
Weightage % |
Topics |
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Computer Networks and Cloud
Computing |
10% |
1 - Data Communication |
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2 - Computer Networks |
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3 - Data Link Layer |
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4 - Network Layer |
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5 Transport Layer |
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6 - Application Layer |
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7 - Wireless Networks |
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8 - Cloud Computing |
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9 - Network Security (Networks
Perspective) |
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10 - Next Generation Networks |
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Programming (C++/Java/Python) |
10% |
1. Programming Fundamentals |
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2. Data Types & Variables |
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3. Operators & Expressions |
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4. Control Structures |
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5. Functions / Methods, |
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6. Input / Output Handling. |
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7. Strings & Text Processing |
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8. Arrays & Collections |
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9. Object-Oriented Programming
(OOP) |
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10. Memory Management Concepts |
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11. Exception & Error Handling |
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12. Modules, Packages &
Libraries |
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13. Advanced Programming Concepts |
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14. Concurrency & Parallelism
(Introductory) |
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15 Debugging, Testing &
Optimization |
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16. Software Development Practices |
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Data Structures & Algorithms |
10% |
1 - Foundations of Data Structure
and Algorithms |
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2 - Linear Data Structures |
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3 - Non-Linear Data Structures |
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4 - Searching Algorithms |
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5 - Sorting Algorithms |
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6 - Hashing |
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7 - Tree Algorithms |
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8 - Graph Algorithms |
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9 - Algorithm Design Techniques |
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10 - Advanced Data Structures |
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11 - String Algorithms |
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12 - Complexity & Optimization |
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Operating Systems |
5% |
1. Introduction to Operating
Systems |
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2. Operating System Structures |
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3. Process Management |
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4. CPU Scheduling |
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5. Thread Management |
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6. Concurrency &
Synchronization |
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7. Deadlocks |
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8. Memory Management |
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9. File System Management |
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10. Secondary Storage Management |
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11. Input / Output Systems |
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12. Protection & Security |
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Software Engineering |
10% |
1. Introduction to Software
Engineering |
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2 Software Process Models |
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3. Agile Software Development |
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4. Software Requirements
Engineering |
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5. Software Project Management |
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6. Software Design |
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7. Software Architecture |
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8. User Interface Design |
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9. Software Implementation &
Coding |
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10. Software Testing |
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11. Software Maintenance &
Evolution |
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12. Software Quality Assurance |
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13. Software Metrics &
Measurement |
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14. Software Configuration
Management |
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15. Software Risk Management |
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16. Software Security Engineering |
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Web Development |
10% |
1. Introduction to Web Development |
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2. Web Architecture &
Protocols |
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3. HTML Fundamentals |
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4. CSS Fundamentals |
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5. Advanced CSS & Responsive
Design |
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6. JavaScript Fundamentals |
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7. Advanced JavaScript |
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8. Frontend Frameworks &
Libraries |
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9. Backend Development
Fundamentals |
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10. Server-Side Programming |
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11. Databases for Web Applications |
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12. Web Security |
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13. Web Performance &
Optimization |
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14. Web Testing & Debugging |
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15. Deployment & Hosting |
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16. Web APIs & Integration |
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17. Modern Web Development
Practices |
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AI / Machine Learning and Data Analytics |
10% |
1. Introduction to AI, ML &
Data Analytics |
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2. Mathematical Foundations |
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3. Python for AI & Data
Analytics |
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4. Data Collection & Pre-processing |
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5. Exploratory Data Analysis (EDA) |
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6. Supervised Learning |
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7. Ensemble Learning |
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8. Unsupervised Learning |
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9. Model Evaluation &
Validation |
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10. Feature Engineering &
Selection |
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11. Deep Learning Fundamentals |
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12. Advanced Deep Learning |
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13. Natural Language Processing
(NLP) |
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14. Computer Vision |
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15. Big Data Analytics
(Introductory) |
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16. Model Deployment & MLOps
Basics |
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17. AI Ethics, Security &
Privacy |
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Cyber Security |
5% |
1. Introduction to Cyber Security |
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2. Security Fundamentals &
Principles |
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3. Cryptography Basics |
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4. Network Security |
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5. Operating System Security |
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6. Web Application Security |
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7. Malware & Attack Techniques |
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8. Authentication & Access
Control |
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9. Secure Software Development |
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10. Wireless & Mobile Security |
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11. Cloud & Virtualization
Security |
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12. Digital Forensics |
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13. Incident Response &
Management |
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14. Security Monitoring &
Auditing |
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15. Cyber Laws & Ethics |
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16. Emerging Trends in Cyber
Security |
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Databases |
10% |
1. Introduction to Database
Systems |
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2. Database System Architecture |
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3. Data Models |
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4. Relational Database Concepts |
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5. Relational Algebra &
Calculus |
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6. Structured Query Language (SQL) |
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7. Advanced SQL |
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8. Database Design &
Normalization |
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9. Transaction Management |
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10. Concurrency Control |
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11. Recovery Management |
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12. Indexing & File
Organization |
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13. Query Processing &
Optimization |
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14. Database Security |
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15. Distributed Databases |
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16. NoSQL & Modern Databases |
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17. Data Warehousing & Data
Mining (Introductory) |
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Problem Solving And Analytical
Skills |
20% |
1. Introduction to Problem Solving |
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2. Problem Understanding &
Analysis |
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3. Logical Reasoning Fundamentals |
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4. Algorithms & Flow Control |
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5. Data Representation &
Abstraction |
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6. Pattern Recognition &
Generalization |
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7. Mathematical & Quantitative
Reasoning |
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8. Algorithmic Thinking |
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9. Critical Thinking &
Decision Making |
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10. Debugging & Error Analysis |
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11. Complexity & Efficiency
Awareness |
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12. Problem Solving Using
Programming |
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13. Data-Driven Problem Solving |
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14. Creative & Innovative
Thinking |
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15. Real-World Problem Solving |
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16. Communication &
Documentation of Solutions |
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Syllabus Download PDF Click here
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