Overview: If you are planning to pursue BCA or B.Tech CSE, etc, through CUET, Computer Science will be one of your domain subjects. Learn the detailed CUET Computer Science Syllabus 2025, including Python programming, database theory, networking, exam pattern, and reference books.
The CUET participating colleges offer a variety of UG programmes in computer science specialisation, such as B.Sc, B.Tech courses, BCA, and so on. Get insights into the CUET computer science syllabus 2025, to know the important chapters and plan your exam preparation.
Important facts about CUET Computer Science Syllabus 2025
The National Testing Agency releases the CUET computer science syllabus 2025, which is followed by all CUET central, state, deemed, and private universities. The CUET CS syllabus covers topics studied till the 12th grade.
The Computer Science exam for the CUET 2025 entrance is divided into sections A and B (B1 and B2).
Section A requires answering all 15 questions about computer science and information practises.
Section B1 will include 35 computer science questions, with just 25 of those questions to be attempted.
Section B2 will include 35 questions about information practises, but only 25 must be answered.
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.
Database Theory
Database Concepts Introduction to database concepts, the difference between database and file system, relational data model: the concept of domain, tuple, relation, keys - candidate key, primary key, alternate key, foreign key;
Relational algebra: selection, projection, union, set difference and cartesian product
SQL stands for 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
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.
Chapter 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
Chapter 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.
Chapter 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.
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, Implementing the Map Abstract Data Type.
Chapter 6: Understanding Data
Data and its purpose, collection and organization; understanding data using statistical methods: mean, median, standard deviation, variance; data interpretation; visualization of data.
Chapter 7: Database Concepts
Introduction to database concepts, the difference between database and file system, relational data model: the concept of domain, tuple, relation, keys - candidate key, primary key, alternate key, foreign key;
Relational algebra: selection, projection, union, set difference and cartesian product
CUET Computer Science Syllabus: Chapter 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
Chapter 9: Computer Networks
Introduction to computer networks, Evolution of networking,
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, and Order by.
Operations on Relations - Union, Intersection, Minus, Cartesian Product, JOIN
Chapter 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, scalar value; mathematical operations; Head and Tail functions; Selection, Indexing, and Slicing.
DataFrames: creation - from the dictionary of Series, list of dictionaries, 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, Head and Tail functions; Joining, Merging and Concatenations.
Importing/Exporting Data between CSV files and DataFrames.
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.
Chapter 4: Plotting Data using Matplotlib
Purpose of plotting; drawing and saving the following types of plots using Matplotlib – line plot, bargraph, histogram, pie chart, frequency polygon, box plot, and scatter plot.
Customizing plots: color, style (dashed, dotted), width; adding label, title, and legend in plots.
Chapter 5: Introduction to Computer Networks
Introduction to Networks, Types of networks: LAN, MAN, WAN.
Digital footprint, Etiquettes for Net surfing and for communicating through social media, data protection, Intellectual Property Rights (IPR) and their violation, plagiarism licensing and copyrights, Free and Open Source Software (FOSS), Cybercrime and cyber laws, hacking, phishing, cyberbullying, Overview of Indian IT Act, preventing cybercrime.
E-waste its a hazard and management
Awareness about health concerns related to the usage of technology like effect on eyesight, physiological issues, and ergonomic aspects.
Knowing the CUET exam pattern not only helps you comprehend the concept of the CUET computer science syllabus and marking scheme better but also gives you a basic notion of the exam's difficulty level.
Particulars
Description
Exam Duration
60 minutes
No. of questions to be attempted
50 out of 50
Exam mode
Computer-based test
Total Marks
250
Medium of exam
English, Bengali, Hindi, Kannada, Malayalam, Urdu, Odia, Telegu, Tamil, Punjabi, Assamese, Marathi and Gujarati
Types of questions
Multiple Choice Questions (MCQs)
Reference Books for CUET UG Computer Science Syllabus 2025
The CUET preparation books are of the utmost significance to cover the exam. You can find a list of the best books for CUET Computer Science syllabus preparation below:
Book Name
Author/Publisher
Computer Science with Python
Rachna Sagar
Computer Science Textbook for Class 12th
NCERT
Computer Science: A Modern Approach
Sumita Arora
In conjunction with Rachna Sagar's Computer Science Class 12
Rachna Sagar
Go To Guide for CUET (UG) Computer Science with 10 Practice Sets