Computer Science / Information Practices
Subject code 308 · domain paper · The bulletin prints “Information Practices”; the school subject is Informatics Practices.
Each of those rules names Computer Science / Information Practices outright — no combination of the other papers reaches them. That is the whole case for spending one of five slots on it.
The paper at a glance
Computer Science / Information Practices carries the subject code 308. The syllabus described here is the one published for 2026-27.
One syllabus document serves two kinds of students: those who studied Computer Science in Class 12 and those who studied Informatics Practices. The information bulletin calls the paper "Information Practices"; the syllabus cover and the school subject both say "Informatics Practices". They mean the same thing.
How the syllabus is organised
The document is laid out in three sections — Section A (four topics), Section B1: Computer Science (eleven topics) and Section B2: Informatics Practices (seven topics). Section A is the shared ground. Section B then appears in two versions, and a candidate works with the one that matches their school subject. Within each section the topics are simply numbered 1, 2, 3 rather than called units.
The syllabus itself is a list of topics only. It does not print question counts, marks, negative marking or timing, and it does not spell out how many questions come from each section. Read it alongside the exam pattern.
Section A: the common part
Section A is short and stays with material both school courses share: relational databases, SQL and the basics of networking. There is no Python in it.
| Topic | What it covers |
|---|---|
| 1: Database Concepts | Introduction to database concepts; difference between a database and a file system; relational data model — domain, tuple, relation, and keys (candidate, primary, alternate, foreign); relational algebra — selection, projection, union, set difference and cartesian product |
| 2: Structured Query Language – I | Advantages of SQL; Data Definition, Data Query and Data Manipulation Language; introduction to MySQL, creating a database, data types; CREATE TABLE, DROP TABLE, ALTER TABLE; SELECT, FROM, WHERE; 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 and ORDER BY; operations on relations — union, intersection, minus, cartesian product, JOIN |
| 4: Computer Networks | Introduction to computer networks and the evolution of networking; network types — LAN, WAN, MAN; network devices — modem, Ethernet card, repeater, hub, switch, router, gateway; topologies — mesh, ring, bus, star and tree; basic concept of MAC and IP address; difference between the Internet and the web |
The SQL topics are specific down to the function names — POWER(), ROUND(), MOD(), the text functions, the date functions and the aggregates — so this is one of the few places where the syllabus tells you exactly which built-ins to know.
Section B1: Computer Science
Eleven topics. The first six are the programming and data-structures half of the Class 12 Computer Science course; the last five are databases, networks and security.
| Topic | What it covers |
|---|---|
| 1: Exception and File Handling in Python | Exception handling — syntax errors, exceptions, need for exception handling, user-defined exceptions, raising, handling and catching exceptions, try-except-else and try-finally clauses, recovering and continuing with finally, built-in exception classes; file handling — text and binary files, file types, opening and closing files, reading and writing text files, reading and writing binary files with the pickle module, file access modes, setting offsets in a file |
| 2: Stack | Stack (list implementation) — introduction to stack (LIFO operations), PUSH and POP and their implementation in Python; prefix, infix and postfix notations; evaluating arithmetic (postfix) expressions using a stack; conversion of infix to postfix |
| 3: Queue | Queue (list implementation) — introduction to queue (FIFO), INSERT and DELETE operations and their implementation in Python; introduction to deque and its implementation in Python |
| 4: Searching | Sequential search, binary search, analysis of both; dry run to identify best, worst and average cases; implementation of searching techniques in Python; hashing — hash functions, collision resolution |
| 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 |
| 6: Understanding Data | Data and its purpose, collection and organisation; understanding data using statistical methods — mean, median, mode (measures of central tendency), range, standard deviation and variance (measures of variability); data interpretation |
| 7: Database Concepts | Introduction to database concepts; difference between a database and a file system; relational data model — domain, tuple, relation, and keys (candidate, primary, alternate, foreign); relational algebra — selection, projection, union, set difference and cartesian product |
| 8: Structured Query Language | Advantages of SQL; Data Definition, Data Query and Data Manipulation Language; introduction to MySQL, creating a database, data types and constraints in MySQL; CREATE TABLE, DROP TABLE, ALTER TABLE; SELECT, FROM, WHERE; 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 and ORDER BY; operations on relations — union, intersection, minus, cartesian product, JOIN |
| 9: Computer Networks | Introduction to computer networks and the evolution of networking; network types — LAN, WAN, MAN; network devices — modem, Ethernet card, repeater, hub, switch, router, gateway; topologies — mesh, ring, bus, star and tree; basic concept of MAC and IP address; difference between the Internet and the web; Domain Name System |
| 10: Data Communication | Concept and types of data communication, switching techniques; communication media — wired (twisted pair, co-axial, Ethernet cable, optical fibre), introduction to mobile telecommunication technologies, wireless (Bluetooth, WLAN, infrared, microwave); network protocols — need, categorisation and examples, HTTP, FTP, IP, PPP, electronic mail protocol; concept of channel, bandwidth (Hz, KHz, MHz) and data transfer rate (bps, Kbps, Mbps, Gbps, Tbps) |
| 11: Security Aspects | Threats and prevention — viruses, worms, Trojan horse, spam, cookies, adware, firewall, http versus https; network security concepts — firewall, cookies, hackers and crackers; antivirus and how it works; network security threats — denial of service, intrusion problems, snooping, eavesdropping |
Topics 7, 8 and 9 — Database Concepts, Structured Query Language and Computer Networks — repeat Section A almost word for word. The B1 versions add a little: constraints in MySQL under SQL, and the Domain Name System under networks. Topic 6, Understanding Data, is a short statistics topic sitting among the programming ones.
Section B2: Informatics Practices
Seven topics. This version is built around data handling in Python — Pandas and Matplotlib — with networks, societal impacts and project-based learning after it.
| Topic | What it covers |
|---|---|
| 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 and ORDER BY; operations on relations — union, intersection, minus, cartesian product, JOIN |
| 2: Data Handling using Pandas – I | Introduction to the Python libraries Pandas, NumPy and Matplotlib; data structures in Pandas — Series and DataFrames; Series — creation from an array, dictionary or scalar value, mathematical operations, head and tail, selection, indexing and slicing; DataFrames — creation from a dictionary of Series, list of dictionaries or text/CSV files, display, iteration, operations on rows and columns (add, select, delete, rename), head and tail, indexing using labels, Boolean indexing, styling and formatting, joining, merging and concatenation; importing and 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 and exporting data between a MySQL database and Pandas |
| 4: Plotting Data using Matplotlib | Purpose of plotting; drawing and saving line plots, bar graphs, histograms, pie charts, frequency polygons, box plots and scatter plots with Matplotlib; customising plots — colour, style (dashed, dotted), width, and adding labels, title and legend |
| 5: Introduction to Computer Networks | Introduction to networks; types — LAN, MAN, WAN; network devices — modem, hub, switch, repeater, router, gateway; topologies — star, bus, tree, mesh; introduction to the Internet, URL, WWW and its applications (web, email, chat, VoIP); website — difference between a website and a webpage, static versus dynamic web pages, web server, hosting; web browsers — commonly used browsers, browser settings, add-ons and plug-ins, cookies |
| 6: Societal Impacts | Digital footprint; etiquette for net surfing and social media communication; 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; health concerns of technology use — effect on eyesight, physiological issues and ergonomic aspects |
| 7: Project Based Learning | Approaches for solving projects; steps in project-based learning; teamwork and the components of teamwork |
Topic 1 repeats the SQL functions from Section A and nothing else, so for a B2 student the SQL functions appear twice. Topics 2 and 3 on Pandas are the most detailed in the whole document, listing the operations on Series and DataFrames one by one. Topic 7, Project Based Learning, has no counterpart in B1.
Choosing between B1 and B2
The school subject you actually studied decides this for you. Compare the two lists:
- Only in B1: exception and file handling in Python, stack, queue, searching, sorting, hashing, data communication and security aspects.
- Only in B2: Pandas, Matplotlib, websites and web browsers, societal impacts, and project-based learning.
- In both, though treated differently: SQL and computer networks.
If your Class 12 course had you write stacks and queues in Python and dry-run sorting algorithms, B1 is your section. If it had you build DataFrames and plot charts with Matplotlib, B2 is. Either way, Section A draws on databases, SQL and networking that both courses share.
What this syllabus does not tell you
The document is a topic list and nothing more. From it you cannot learn:
- how many questions come from Section A and how many from your Section B, or the marks, negative marking and duration — those are on the exam pattern;
- the weightage of any topic, so treat every topic as examinable rather than ranking them;
- how difficult the questions will be, or whether they will be conceptual, code-reading or output-prediction questions;
- which version of Python, MySQL or Pandas is assumed; the document names none;
- which books to use; the syllabus names no textbook;
- how much weight a university gives this paper once you qualify — the programmes that accept it are listed below, but the marks or ranking rule each one applies sits in its own admission bulletin.
For anything about attempt rules or numbers of questions, go to the NTA information bulletin and the exam pattern rather than to this list.
Where this paper can take you
Programmes whose rule can use Computer Science / Information Practices, from the 13 universities whose documents we have read. 4 of them cannot be reached any other way.
B Design (Fashion) [ 2+2 with international credit transfer option] · B Sc (IT) [2+2 with international credit transfer option] · B. Arch. · and 104 more
B.A. (Hons.) Political Science · B.A. (Programme) · B.A. (Hons.) Psychology · and 49 more
Bachelor of Computer Application · Bachelor of Computer Application (Honours/Honours with Research) · Bachelor of Science (Geo- Informatics) · and 16 more
Bachelor of Fine Arts (BFA) · B.A. LL.B. (Hons.) · Five Year Integrated Programme in Management (BBA & MBA) · and 13 more
Bachelor of Arts (Global Studies) · Bachelor of Arts (Hons.) - Economics · Bachelor of Arts (Hons.) - English · and 11 more
B.A. (Hons.) Media and Communication · B.B.A. (Hons.) Business Administration (Puducherry Main Campus) · B.Com. (Hons.) General (Karaikal Campus) · and 8 more
B.Sc. in Forensic Science · Bachelor of Arts (Journalism and Mass Communication) · Bachelor of Business Administration · and 1 more
B.S.–M.S. in Data Science · B.Tech. (Lateral Entry) — thirteen engineering and chemical-technology branches · Bachelor of Computer Application
Integrated B.Sc.–M.Sc. (Chemistry) · Integrated B.Sc.–M.Sc. (Mathematics) · Integrated B.Sc.–M.Sc. (Physics)
B.Sc. Computer Science & Information Technology