CUET Computer Science Syllabus 2025

CUET Computer Science Syllabus 2025- The Common University Entrance Test (CUET), once known as the CUCET, is a requisite exam taken for admission to nearly 400+ universities across India. CUET evaluates aspiring students for various UG programmes.
For the ease of students, the National Testing Agency (NTA) has made available the CUET Computer Science syllabus 2025, along with course materials for other domains, on its official website.
The exam administering organization of CUET, NTA, has notified all candidates that the computer science curriculum will cover only NCERT material for the 12th grade. To develop a comprehensive and efficient preparation plan, students must meticulously review the syllabus and focus on the essential chapters.
For complete coverage of CUET Computer Science Syllabus 2025 you can refer to HitBullseye's Comprehensive CUET Computer Science Study Book
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Important details regarding the CUET computer science exam:
There will be one question paper, including 3 Sections of language, domain subjects & General Test
In the second section, an aspirant can choose 3/4 class XII subjects as per their choice.
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CUET Computer Science Syllabus:
This post will provide you with a concise overview of CUET's comprehensive computer science syllabus. Preparing for the CUET in computer science requires a thorough understanding of the curriculum, making this area a crucial aspect.
The table below provides the detailed syllabus:
S. No.
UNIT
SUB TOPICS
Section A
1
Database Concepts
  • Introduction to database concepts, difference between database and file system, relational data model: concept of domain, tuple, relation, keys - candidate key, primary key, alternate key, foreign key.
  • Relational algebra: selection, projection, union, set difference and cartesian product.
2
Structured Query Language - I
  • Advantages of using Structured Query Language, Data Definition Language, Data Query Language and Data Manipulation Language, Introduction to MySQL, Creating a database using MySQL, DataTypes.
  • Data Definition: CREATE TABLE, DROP TABLE, ALTER TABLE; Data Query: SELECT, FROM, WHERE.
  • Data Manipulation: INSERT, UPDATE, DELETE.
  • Math functions: POWER(), ROUND(), MOD().
  • Text functions: UCASE()/UPPER(), LCASE()/LOWER(), MID()/SUBSTRING()/SUBSTR(), LENGTH(), LEFT(), RIGHT(), INSTR(), LTRIM(), RTRIM(), TRIM().
3
Structured Query Language - II
  • Date Functions: NOW(), DATE(), MONTH(), MONTHNAME(), YEAR(), DAY(), DAYNAME().
  • Aggregate Functions: MAX(), MIN(), AVG(), SUM(), COUNT(); using COUNT(*).
  • Querying and manipulating data using Group by, Having, Order by.
  • Operations on Relations - Union, Intersection, Minus, Cartesian Product, JOIN.
4
Computer Networks
  • Introduction to computer networks, Evolution of networking.
  • Network types: LAN, WAN, MAN.
  • Network devices: Modem, Ethernet Card, Repeater, Hub, Switch, Router, Gateway.
  • Network Topologies: Mesh, Ring, Bus, Star, and Tree topologies.
  • Basic concept of MAC and IP Address. Difference between Internet and web.
Section B1: Computer Science
1
Exception and File Handling in Python
  • Exception Handling: syntax errors, exceptions, need of exception handling, user-defined exceptions, raising exceptions, handling exceptions, catching exceptions, Try-except-else clause, Try-finally clause, recovering and continuing with finally, built-in exception classes.
  • File Handling: text file and binary file, file types, open and close files, reading and writing text files, reading and writing binary files using pickle module, file access modes.
2
Stack
  • Stack (List Implementation): Introduction to stack (LIFO Operations), operations on stack (PUSH and POP) and its implementation in Python. Expressions in Prefix, Infix and Postfix notations, evaluating arithmetic expressions using stack, conversion of Infix expression to Postfix expression.
3
Queue
  • Queue (List Implementation): Introduction to Queue (FIFO), operations on Queue (INSERT and DELETE) and its implementation in Python.
  • Introduction to DQueue and its implementation in Python.
4
Searching
  • Searching: Sequential search, Binary search, Analysis of Sequential and Binary Search. Dry run to identify best, worst and average cases. Implementation of searching techniques in Python.
5
Sorting
  • Overview of sorting techniques, Bubble Sort, Selection Sort and Insertion Sort. Dry run to identify best, worst and average cases. Implementation of sorting techniques in Python.
  • Hashing: Hash Functions, Collision Resolution.
6
Understanding Data
  • Data and its purpose, collection and organization; understanding data using statistical methods: mean, median, standard deviation, variance; data interpretation.
7
Database Concepts
  • Introduction to database concepts, difference between database and file system, relational data model: concept of domain, tuple, relation, keys - candidate key, primary key, alternate key, foreign key.
  • Relational algebra: selection, projection, union, set difference and cartesian product.
8
Structured Query Language
  • Advantages of using Structured Query Language, Data Definition Language, Data Query Language and Data Manipulation Language, Introduction to MySQL, Creating a database using MySQL, Data Types.
  • Data Definition: CREATE TABLE, DROP TABLE, ALTER TABLE.
  • Data Query: SELECT, FROM, WHERE.
  • Data Manipulation: INSERT, UPDATE, DELETE.
  • Math functions: POWER(), ROUND(), MOD().
  • Text functions: UCASE()/UPPER(), LCASE()/LOWER(), MID()/SUBSTRING()/SUBSTR(), LENGTH(), LEFT(), RIGHT(), INSTR(), LTRIM(), RTRIM(), TRIM().
  • Date Functions: NOW(), DATE(), MONTH(), MONTHNAME(), YEAR(), DAY(), DAYNAME().
  • Aggregate Functions: MAX(), MIN(), AVG(), SUM(), COUNT(); using COUNT(*).
  • Querying and manipulating data using Group by, Having, Order by.
  • Operations on Relations - Union, Intersection, Minus, Cartesian Product, JOIN.
9
Computer Networks
  • Introduction to computer networks, Evolution of networking.
  • Network types: LAN, WAN, MAN.
  • Network devices: Modem, Ethernet Card, Repeater, Hub, Switch, Router, Gateway.
  • Network Topologies: Mesh, Ring, Bus, Star, and Tree topologies.
  • Basic concept of MAC and IP Address.
  • Difference between Internet and web.
10
Data Communication
  • Concept of communication, Types of Data Communication, switching techniques.
  • Communication Media: Wired Technologies – Twisted pair cable, Co-axial cable, Ethernet Cable, Optical Fibre.
  • Introduction to mobile telecommunication technologies.
  • Wireless Technologies – Bluetooth, WLAN, Infrared, Microwave.
  • Network Protocol: Need for Protocol, Categorization and examples of protocol, HTTP, FTP, IP, PPP; electronic mail protocol.
  • Concept of Channel, Bandwidth (Hz, KHz, MHz) and Data Transfer rate (bps, Kbps, Mbps, Gbps, Tbps).
  • Threats and prevention: Viruses, Worms, Trojan horse, Spam, Cookies, Adware, Firewall, http vs https.
  • Network Security Concepts: Firewall, Cookies, Hackers and Crackers.
  • Antivirus and their workings.
  • Network security threats: Denial of service, Intrusion problems, Snooping, Eavesdropping.
Section B2: Informatics Practices
1
Database Query using SQL
  • Math functions: POWER(), ROUND(), MOD().
  • Text functions: UCASE()/UPPER(), LCASE()/LOWER(), MID()/SUBSTRING()/SUBSTR(), LENGTH(), LEFT(), RIGHT(), INSTR(), LTRIM(), RTRIM(), TRIM().
  • Date Functions: NOW(), DATE(), MONTH(), MONTHNAME(), YEAR(), DAY(), DAYNAME().
  • Aggregate Functions: MAX(), MIN(), AVG(), SUM(), COUNT(); using COUNT(*).
  • Querying and manipulating data using Group by, Having, Order by.
  • Operations on Relations - Union, Intersection, Minus, Cartesian Product, JOIN.
2
Data Handling using Pandas – I
  • Introduction to Python libraries: Pandas, NumPy, Matplotlib.
  • Data structures in Pandas - Series and DataFrames.
  • Series: Creation of Series from an array, dictionary, or scalar value; mathematical operations; Head and Tail functions; Selection, Indexing, and Slicing.
  • DataFrames: creation from dictionary of Series, list of dictionaries, or Text/CSV files; display; iteration; Operations on rows and columns: add, select, delete, rename; Head and Tail functions; Indexing using Labels, Boolean Indexing; Styling & Formatting data; Joining, Merging and Concatenations.
  • Importing/Exporting Data between CSV files and DataFrames.
3
Data Handling using Pandas – II
  • Descriptive Statistics: max, min, count, sum, mean, median, mode, quartile, standard deviation, variance.
  • DataFrame operations: Aggregation, group by, sorting, deleting and renaming index, pivoting.
  • Handling missing values – dropping and filling.
  • Importing/Exporting Data between MySQL database and Pandas.
4
Plotting Data using Matplotlib
  • Purpose of plotting; drawing and saving the following types of plots using Matplotlib – line plot, bar graph, histogram, pie chart, frequency polygon, box plot, and scatter plot.
  • Customizing plots: color, style (dashed, dotted), width; adding label, title, and legend in plots.
5
Introduction to Computer Networks
  • Introduction to Networks, Types of networks: LAN, MAN, WAN.
  • Network Devices: modem, hub, switch, repeater, router, gateway.
  • Network Topologies: Star, Bus, Tree, Mesh.
  • Introduction to Internet, URL, WWW, and its applications – Web, email, Chat, VoIP.
  • Website: Introduction, difference between a website and webpage, static vs dynamic webpage, webserver, and hosting of a website.
  • Web Browsers: Introduction, commonly used browsers, browser settings, add-ons and plug-ins, cookies.
6
Societal Impacts
  • Digital footprint, etiquettes for net surfing and communicating through social media, data protection, Intellectual Property Rights (IPR) and their violation, plagiarism licensing and copyrights, Free and Open Source Software (FOSS), creative commons.
  • Cybercrime and cyber laws, hacking, phishing, cyberbullying, overview of the Indian IT Act, preventing cybercrime.
  • E-waste: hazards and management.
  • Awareness about health concerns related to technology usage – effects on eyesight, physiological issues, and ergonomic aspects.
The next question that naturally comes after thoroughly knowing the CUET computer science syllabus is how to prepare for the exam.
By supporting you in comprehending the critical steps in preparation and empowering you to come up with the ideal preparation method, this article will try to assist you.
How do I get ready for the Computer Science CUET?
A strategy planning and development is acknowledging your own capabilities and available time. Once you recognize these elements, you're prepared to implement any plan. Choosing the most effective preparation strategy is paramount; innumerable tactics and ideas exist for Computer Science preparation at CUET. Let's explore key factors you may find useful to develop a robust plan for your computer science (CUET) preparation..
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Detailed knowledge of the curriculum:
A thorough understanding of the CUET computer science course is crucial for planning effectively. It's important to grasp all the themes, units, and sub-units as they form the syllabus of class 12. Neglecting any portion is inadvisable, as each one holds equal importance.
Thorough understanding of the exam format:
This section provides an overview of the number and types of questions for each unit, already covered in earlier parts of this text. It helps you gauge the value and weight of each unit, enabling you to set priorities and differentiate between the chapters you comprehend and those you don't. Consider this a vital and astute step in your preparation process, as it will assist you in planning your strategy to perfection.
Custom-made planning approach:
While one approach may work for one person, it might not be as effective for another. Hence, it is crucial to develop a planning strategy tailored to your specific needs. Every student must devise an appropriate schedule that aligns with their strengths and talents. By creating a plan and adhering to it with commitment and reliability, you'll be better equipped to succeed on the exam day.
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Make changes and do practice exams:
The key to success is simple: practice, practice, practice. As your exam approaches, focus less on learning new material and more on reviewing completed coursework and taking practice exams. By immersing yourself in the actual exam experience, you'll feel more assured and confident come test day. Once you've completed the CUET computer science syllabus, it's highly recommended that you continue your review with a mock exam. Remember, the more you practice, the better-equipped you'll be to master this challenge!.
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