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CUET (UG) Computer Science\Information Practices Syllabus: Check the Latest Syllabus

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CUET (UG) Computer Science\Information Practices Syllabus 2024 PDF Download

Candidates must be familiar with the CUET (UG) Computer Science\Information Practices Syllabus to pursue further Computer Science\Information Practices education. Click here to access the CUET (UG) Computer Science\Information Practices Syllabus 2024 PDF.


CUET (UG) Computer Science\Information Practices Syllabus 2024

The CUET (UG) Computer Science\Information Practices Syllabus for the CUET (UG) 2024 is available by the National Testing Agency. The CUET (UG) Computer Science\Information Practices Syllabus is available for review from the link below. The CUET (UG) 2024 Computer Science\Information Practices syllabus defines and describes each unit covered on the CUET (UG) 2024 Computer Science\Information Practices exam.

Academic year:

NTA Entrance Exam Computer Science\Information Practices Revised Syllabus

NTA Entrance Exam Computer Science\Information Practices and their Unit wise marks distribution

Units and Topics

#Unit/TopicWeightage
I  Computer Science 
1  Exception and File Handling in Python 
2  Stack 
3  Queue 
4  Searching 
5  Sorting 
6  Understanding Data 
7  Database Concepts 
8  Structured Query Language (SQL) 
9  Computer Networks 
10  Data Communication 
11  Security Aspects 
II  Information Practices 
12  Database Query using SQL 
13  Data Handling Using Pandas – I 
14  Data Handling Using Pandas – II 
15  Plotting Data Using Matplotlib 
16  Introduction to Computer Networks 
17  Societal Impacts 
 Total -
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Syllabus

NTA Entrance Exam Computer Science\Information Practices Syllabus for Chapter 1: Computer Science

1 Exception and File Handling in Python
  • Introduction of Exception Handling in Python  
  • Syntax Errors  
  • Exceptions  
  • Built-in Exceptions  
    • Built-in exceptions in Python
    • user-defined exceptions
  • Raising Exceptions  
    • The raise Statement
    • The assert Statement
    • Program: Use of assert statement
  • Handling Exceptions  
    • Exception handling
    • Need for Exception Handling
    • Process of Handling Exception
    • Catching exceptions
      ⇒ Program: Using try..except block
      ⇒ Program: Use of multiple except clauses
      ⇒ Program: Use of except without specifying an exception
    • try...except…else clause
      ⇒ Program: Use of else clause
  • Finally Clause  
    • Finally Clause
      ⇒ Program: Use of finally clause
    • Recovering and continuing with finally clause
      ⇒ Program: Recovering through finally clause
  • Introduction to Files  
  • Types of Files in Python  
    1. Text file
    2. Binary files
    3. CSV files
  • Opening and Closing a Text Files  
    • Opening a file: open ()
    • Closing a file: close ()
    • Opening a file using with clause
    • File access modes
  • Writing to a Text File  
    • The write () method
    • The writelines () method
  • Reading from a Text File  
    • The read() method
    • The readline([n]) method
    • The readlines() method
      ⇒ Program: Writing and reading to a text file
  • Setting Offsets in a File  
    • The tell() method
    • The seek() method
      ⇒ Application of seek() and tell()
  • Creating and Traversing a Text File (Data Manipulation)  
    • Creating a file and writing data
      ⇒ Program: To create a text file and write data in it
    • Traversing a file and displaying data
      ⇒ Program: To display data from a text file
      ⇒ Program: To perform reading and writing operation in a text file
  • The Pickle Module  
    • Pickle
    • Methods of pickle files
    1. The dump() method
      ⇒ Program: Pickling data in Python
    2. The load() method
      ⇒ Program: Unpickling data in Python
    3. File handling using the pickle module
      ⇒ Program: To perform basic operations on a binary file using the pickle module
2 Stack
  • Stack and Queue in Data Structure  
  • Notations for Arithmetic Expressions  
    • Infix, Prefix and Postfix Notations
  • Conversion from Infix to Postfix Notation  
    • Algorithm: Conversion of expression from infix to postfix notation
  • Evaluation of Postfix Expression  
    • Algorithm: Evaluation of postfix expression
3 Queue
  • Stack and Queue in Data Structure  
  • Introduction to Deque  
    • Applications of Deque
    • Operations on Deque
  • Implementation of Deque Using Python  
    • Program: Implementation of Deque in Python
4 Searching
  • Searching in Data Structure  
    • Introduction to searching 
    • Linear search 
    • Binary search
  • Linear Search  
    • Sequential search
    • Algorithm: Linear Search
    • Analysis of Sequential Search
  • Binary Search  
    • Algorithm: Binary Search
    • Applications of Binary Search
    • Analysis of Binary Search
  • Dry Run to Identify Best, Worst and Average Cases  
  • Implementation of Searching Techniques in Python  
  • Search by Hashing  
    • Hash functions
    • Collision
    • Collision resolution
    • Implementing the Map Abstract Data Type
5 Sorting
  • Sorting in Data Structure  
    • Introduction to Sorting 
    • Bubble Sorting 
  • Bubble Sort  
    • Algorithm: Bubble Sort
    • Program: Implementation of bubble sort using Python
  • Selection Sort  
    • Algorithm: Selection Sort
    • Program: Implementation of selection sort using Python
  • Insertion Sort  
    • Algorithm: Insertion Sort
  • Dry Run to Identify Best, Worst and Average Cases  
  • Time Complexity of Algorithms  
  • Implementation of Sorting Techniques in Python  
6 Understanding Data
  • Introduction to Data  
  • Importance of Data  
  • Types of Data  
    1. Structured Data
    2. Unstructured Data
  • Data Collection  
  • Data Storage  
  • Data Processing  
  • Statistical Techniques for Data Processing  
    • Variance
    • Data interpretation
    • Visualization of data
    • Measures of Central Tendency for Data Processing  
      1. Mean
      2. Median
      3. Mode
    • Measures of Variability  
      1. Range
      2. Standard deviation
7 Database Concepts
  • Introduction to Database Concepts  
    • Need for database concepts in python
  • Difference Between Database and File System  
  • File System  
  • Limitations of a File System  
    1. Difficulty in Access
    2. Data Redundancy
    3. Data Inconsistency
    4. Data Isolation
    5. Data Dependence
    6. Controlled Data Sharing
  • Database Management System Software (DBMS)  
  • Applications of DBMS  
    • Railway Reservation System
    • Library Management System
    • Banking
    • Universities and Colleges
    • Credit Card Transactions
    • Social Media Sites
  • File System to Database Management System (DBMS)  
  • Key Concepts in Database Management System (DBMS)  
    1. Database Schema
    2. Data Constraint
    3. Meta-data or Data Dictionary
    4. Database Instance
    5. Query
    6. Data Manipulation
    7. Database Engine
  • Relational Data Model  
  • Terminologies in Relational Data Model  
    1. Attribute
    2. Tuple
    3. Domain
    4. Degree
    5. Cardinality
  • Properties of a Relational Data Model  
  • Keys in a Relational Database  
    1. Candidate Key
    2. Primary Key
    3. Alternate Key
    4. Composite Primary Key
    5. Foreign Key
  • Relational Algebra  
    • Selection
    • Projection
    • Union
    • Set Difference
    • Cartesian Product
8 Structured Query Language (SQL)
  • Introduction of Structured Query Language (SQL)  
  • Structured Query Language (SQL)  
    • Structured Query Language (SQL)
    • Installing MySQL
  • Data Types and Constraints in MySQL  
    • Data type of Attribute
      1) char(n),
      2) varchar(n),
      3) int,
      4) float,
      5) date
    • Constraints - not null, unique, primary key
  • SQL for Data Definition  
    • CREATE Database
    • Use database
    • Show database
    • Drop database
    • Show tables
    • CREATE Table
    • Describe Table
    • Drop Tables
    • ALTER Table
    1. Add primary key to a relation
    2. Add foreign key to a relation
    3. Add constraint UNIQUE to an existing attribute
    4. Add an attribute to an existing table
    5. Modify datatype of an attribute
    6. Modify constraint of an attribute
    7. Add default value to an attribute
    8. Remove an attribute
      ⇒ Remove primary key from the table
    • DROP Statement
  • SQL for Data Manipulation  
    • INSERTION of Records
  • SQL for Data Query  
    • SELECT Statement
    • QUERYING using Database OFFICE
      (A) Retrieve selected columns
      (B) Renaming of columns
      (C) Distinct Clause
      (D) WHERE Clause
      (E) Membership operator IN
      (F) ORDER BY Clause
      (G) Handling NULL Values
      (H) Substring pattern matching
  • Data Updation and Deletion  
    • Data Updation
    • Data Deletion
  • Functions in SQL  
    • Single Row Functions
    1. Math/ Numeric Functions: POWER(), ROUND(), MOD().
    2. String Functions/ Text functions: UCASE ()/UPPER (), LCASE ()/LOWER (), MID ()/SUBSTRING ()/SUBSTR (), LENGTH (), LEFT (), RIGHT (), INSTR (), LTRIM (), RTRIM (), TRIM ().
    3. Date Functions: NOW (), DATE (), MONTH (), MONTHNAME (), YEAR (), DAY (), DAYNAME ().
    • Aggregate Functions: MAX (), MIN (), AVG (), SUM (), COUNT (); using COUNT
  • GROUP BY Clause in SQL  
    • Querying and manipulating data using Group by, Having, Order by.
  • Operations on Relations  
    • UNION (∪)
    • INTERSECT (∩)
    • MINUS (-)
    • Cartesian Product (X)
  • Using Two Relations in Query  
    • Cartesian product on two tables
    • JOIN on two tables : equi-join and natural join
9 Computer Networks
  • Introduction to Computer Networks  
  • Evolution of Networking  
    • ARPANET, NSFNET, INTERNET
  • Types of Networks  
    • Introduction
    • Local Area Network (LAN)
    • Metropolitan Area Network (MAN)
    • Wide Area Network (WAN)
  • Network Devices  
    • Modem
    • Ethernet Card
    • RJ45
    • Repeater
    • Hub
    • Switch
    • Connector
    • Router
    • Gateway
    • Wifi Card
  • Networking Topologies  
    1. Mesh Topology
    2. Ring Topology
    3. Bus Topology
    4. Star Topology
    5. Tree or Hybrid Topology
  • Types of Networking Topologies  
    1. Mesh Topology
    2. Ring Topology
    3. Bus Topology
    4. Star Topology
    5. Tree or Hybrid Topology
  • Identifying Nodes in a Networked Communication  
    • MAC Address
    • IP Address
  • Internet, Web and the Internet of Things  
    • The World Wide Web (WWW)
  • Network Protocol – DNS (Domain Name System)  
    • Domain name system
    • DNS Server
10 Data Communication
  • Concept of Data Communication  
  • Components of Data Communication  
    • Sender
    • Receiver
    • Message
    • Communication media
    • Protocols
  • Measuring Capacity of Communication Media  
    • Channel
    • Bandwidth (Hz, KHz, MHz)
    • Data Transfer Rate (bps, Kbps, Mbps, Gbps, Tbps)
  • Types of Data Communication  
    • Types of data communication
    1. Simplex Communication
    2. Half-duplex Communication
    3. Full-duplex Communication
  • Switching Techniques  
    • Switching Techniques
    1. Circuit Switching
    2. Packet Switching
  • Transmission Media  
    • Communication media
    • Classification of communication media
    1. Wired Transmission Media
      (A) Twisted Pair Cable
      (B) Coaxial cable
      (C) Optical Fibre
      (D) Ethernet Cable
    2. Wireless Transmission Media
      (A) Radio Waves
      (B) Microwaves
      (C) Infrared waves
    3. Wireless Technologies
      (A) Bluetooth
      (B) Wireless LAN
  • Mobile Telecommunication Technologies  
    • 1G, 2G, 3G, 4G, and 5G
  • Network Protocol  
    • Need for Protocols
11 Security Aspects
  • Network Threats and Its Prevention  
  • Malware  
    • Malware
    1. Virus
    2. Worms
    3. Ransomware
    4. Trojan
    5. Spyware
    6. Adware
    7. Keyloggers
      ⇒ Online Virtual Keyboard Vs On-Screen Keyboard
    8. Modes of Malware distribution
    9. Combating Malware
  • Antivirus  
    • Methods of Malware Identification used by Antivirus
      (A) Signature-based detection
      (B) Sandbox detection
      (C) Data mining techniques
      (D) Heuristics
      (E) Real-time protection
  • Spam  
  • HTTP vs HTTPS  
  • Protection Using Firewall  
    • Firewall
    • Types of Firewall
      1) Network Firewall
      2) Host-based Firewall
  • Cookies  
  • Hackers and Crackers (Hacking)  
    • Hacking
    • Hackers and Crackers
    • Types of hackers
    1. White Hats: Ethical Hacker
    2. Black Hats: Crackers
    3. Grey Hats
  • Network Security  

NTA Entrance Exam Computer Science\Information Practices Syllabus for Chapter 2: Information Practices

12 Database Query using SQL
  • Introduction of Database Query Using SQL  
    • The following four relations:
    1. Inventory
    2. Customer
    3. Sale
    4. Employee
  • Functions in SQL  
    • Single Row Functions
    1. Math/ Numeric Functions: POWER(), ROUND(), MOD().
    2. String Functions/ Text functions: UCASE ()/UPPER (), LCASE ()/LOWER (), MID ()/SUBSTRING ()/SUBSTR (), LENGTH (), LEFT (), RIGHT (), INSTR (), LTRIM (), RTRIM (), TRIM ().
    3. Date Functions: NOW (), DATE (), MONTH (), MONTHNAME (), YEAR (), DAY (), DAYNAME ().
    • Aggregate Functions: MAX (), MIN (), AVG (), SUM (), COUNT (); using COUNT
  • GROUP BY Clause in SQL  
    • Querying and manipulating data using Group by, Having, Order by.
  • Operations on Relations  
    • UNION (∪)
    • INTERSECT (∩)
    • MINUS (-)
    • Cartesian Product (X)
  • Using Two Relations in Query  
    • Cartesian product on two tables
    • JOIN on two tables : equi-join and natural join
13 Data Handling Using Pandas – I
  • Introduction to Python Libraries  
    • NumPy, Pandas and Matplotlib
    • Installing Pandas
    • Data Structure in Pandas - Series and DataFrame
  • A Series  
    • Creation of Series
      (A) Creation of Series from Scalar Values
      (B) Creation of Series from NumPy Arrays
      (C) Creation of Series from Dictionary
    • Accessing Elements of a Series
      (A) Indexing
      (B) Slicing
      (C) Selection
    • Attributes of Series
    • Methods of Series: Head and Tail functions
    • Mathematical Operations on Series
      (A) Addition of two Series
      (B) Subtraction of two Series
      (C) Multiplication of two Series
      (D) Division of two Series
  • DataFrame  
    • DataFrame
    • Creation of DataFrame
      (i) Creation of an empty DataFrame
      (ii) Creation of DataFrame from NumPy ndarrays
      (iii) Creation of DataFrame from List of Dictionaries
      (iv) Creation of DataFrame from Dictionary of Lists
      (v) Creation of DataFrame from Series
      (vi) Creation of DataFrame from Dictionary of Series
    • Operations on rows and columns in DataFrames
      (i) Adding a New Column to a DataFrame
      (ii) Adding a New Row to a DataFrame
      (iii) Selecting Rows or Columns from a DataFrame
      (iv) Deleting Rows or Columns from a DataFrame
      (v) Renaming Row Labels of a DataFrame
      (vi) Renaming Column Labels of a DataFrame
    • Accessing DataFrames Element through Indexing
      (i) Label Based Indexing
      (ii) Boolean Indexing
    • Accessing DataFrames Element through Slicing
      i) Filtering Rows in DataFrames
    • Joining, Merging and Concatenation of DataFrames
      i) Joining
    • Attributes of DataFrames
    • Head and Tail Functions
    • Styling and formatting data
  • Importing and Exporting Data between CSV Files and DataFrames  
    • Importing a CSV file to a DataFrame
    • Exporting a DataFrame to a CSV file
  • Pandas Series Vs NumPy ndarray  
14 Data Handling Using Pandas – II
  • Introduction of Data Handling Using Pandas – II  
    • Case Study
  • Descriptive Statistics  
    • Descriptive Statistics
    1. Calculating Maximum Values
    2. Calculating Minimum Values
    3. Calculating Sum of Values
    4. Calculating Number of Values
    5. Calculating Mean
    6. Calculating Median
    7. Calculating Mode
    8. Calculating Quartile
    9. Calculating Variance
    10. Calculating Standard Deviation
  • Data Aggregations  
  • Sorting in Data Structure  
    • Introduction to Sorting 
    • Bubble Sorting 
  • GROUP BY Functions  
  • Altering the Index  
  • Other DataFrame Operations  
    • Reshaping Data
      (A) Pivot
      (B) Pivoting by Multiple Columns
      (C) Pivot Table
  • Handling Missing Values  
    • Checking Missing Values
    • Dropping Missing Values
    • Estimating Missing Values
  • Import and Export of Data between Pandas and MySQL  
    • Importing Data from MySQL to Pandas
    • Exporting Data from Pandas to MySQL
  • Deleting and Renaming Index  
15 Plotting Data Using Matplotlib
  • Introduction of Plotting Data Using Matplotlib  
  • Plotting Using Matplotlib  
  • Customisation of Plots  
    • Marker
    • Colour
    • Linewidth and Line Style (Dashed, dotted)
    • Width
    • Add label, title, and legend in plots
  • The Pandas Plot Function (Pandas Visualisation)  
    • Plotting a Line chart
    • Plotting Bar Chart 
    • Plotting Histogram
    • Plotting Scatter Chart
    • Plotting Quartiles and Box plot
    • Plotting Pie Chart
16 Introduction to Computer Networks
  • Introduction to Computer Networks  
  • Types of Networks  
    • Introduction
    • Local Area Network (LAN)
    • Metropolitan Area Network (MAN)
    • Wide Area Network (WAN)
  • Network Devices  
    • Modem
    • Ethernet Card
    • RJ45
    • Repeater
    • Hub
    • Switch
    • Connector
    • Router
    • Gateway
    • Wifi Card
  • Networking Topologies  
    1. Mesh Topology
    2. Ring Topology
    3. Bus Topology
    4. Star Topology
    5. Tree or Hybrid Topology
  • Internet  
    • Introduction
    • History Of Internet
  • Applications of Internet  
    • The World Wide Web (WWW)
    • Electronic mail (Email)
    • Chat
    • Voice Over Internet Protocol (VoIP)
  • Website  
    • Purpose of a Website
  • Web Page  
    • Static and Dynamic Web Pages
  • Web Servers  
  • Website Hosting  
    • Web hosting
  • Browsers  
    • Browser Settings
    • Add-Ons and Plug-ins
    • Cookies
17 Societal Impacts
  • Introduction of Societal Impacts  
  • Digital Footprints  
  • Digital Society and Netizen  
    • Etiquettes for Net surfing and for communicating through social media
    • Net Etiquettes
      (A) Be Ethical
      (B) Be Respectful
      (C) Be Responsible
    • Communication Etiquettes
      (A) Be Precise
      (B) Be Polite
      (C) Be Credible
    • Social Media Etiquettes
      (A) Be Secure
      (B) Be Reliable
  • Data Protection  
  • Intellectual Property Right  
    1. Copyright
    2. Patent
    3. Trademark
  • Software Licensing  
  • Violation of Intellectual Property Right (IPR)  
    1. Plagiarism
    2. Copyright Infringement
    3. Trademark Infringement
  • Public Access and Open Source Software  
  • Creative Commons  
  • Cyber Crimes  
    • Cyber Crime
    1. Hacking
    2. Phishing and Fraud Emails
      (A) Identity Theft
    3. Ransomware
    4. Combatting and Preventing Cyber Crime
  • Indian Information Technology Act (IT Act)  
    • Salient features of IT Act
  • E-waste: Hazards and Management  
    • Impact of e-waste on the environment
    • Impact of e-waste on humans
    • Management of e-waste: Reduce, Reuse, Recycle
    • E-waste Management in India
  • Impact on Health  
    • Awareness about health concerns related to the usage of technology like effect on eyesight, physiological issues, and ergonomic aspects.
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