UK Board Class 11 Computer Science Syllabus 2025-26: Download FREE PDF

The Uttarakhand Board of School Education (UBSE) has officially released the Class 11 Computer Science syllabus for the academic session 2025-26, offering students a comprehensive, logic-based introduction to the world of computing and programming. This curriculum is strategically designed to prepare students for the 70-mark theory paper and the mandatory 30-mark practical assessment, which focuses on hands-on coding and project work.

This comprehensive framework is designed to equip students with a robust conceptual understanding of algorithmic thinking and computational practices. By bridging the gap between theoretical logic and practical application, the syllabus fosters the technical proficiency and ethical awareness necessary for higher education in technology and professional success in the digital age.

UK Board Class 11 Computer Science Syllabus 2026: Key Highlights

UBSE Class 11 Computer Science Syllabus 2025-26

1. Learning Outcomes Students should be able to: 

a) develop basic computational thinking 

b) explain and use data types 

c) appreciate the notion of algorithms 

d) develop a basic understanding of computer systems- architecture and operating system 

e) explain cyber ethics, cyber safety, and cybercrime 

f) understand the value of technology in societies along with consideration of gender and disability issues.

2. Distribution of Marks  

3. Unit wise Syllabus 

Unit 1: Computer Systems and Organisation 

● Basic computer organisation: Introduction to Computer System, hardware, software, input device, output device, CPU, memory (primary, cache and secondary), units of memory (bit, byte, KB, MB, GB, TB, PB) 

● Types of software: System software (Operating systems, system utilities, device drivers), programming tools and language translators (assembler, compiler, and interpreter), application software ● Operating System(OS): functions of the operating system, OS user interface 

● Boolean logic: NOT, AND, OR, NAND, NOR, XOR, truth tables and De Morgan’s laws, Logic circuits 

● Number System: Binary, Octal, Decimal and Hexadecimal number system; conversion between number systems 

● Encoding Schemes: ASCII, ISCII, and Unicode (UTF8, UTF32) 

Unit 2: Computational Thinking and Programming - I 

● Introduction to Problem-solving: Steps for Problem-solving (Analyzing the problem, developing an algorithm, coding, testing, and debugging), representation of algorithms using flowchart and pseudocode, decomposition 

● Familiarization with the basics of Python programming: Introduction to Python, Features of Python, executing a simple “hello world" program, execution modes: interactive mode and script mode, Python character set, Python tokens( keyword, identifier, literal, operator, punctuator), variables, concept of l-value and r-value, use of comments 

● Knowledge of data types: Number(integer, floating point,complex), boolean, sequence(string, list, tuple), None, Mapping(dictionary), mutable and immutable data types. 

● Operators: arithmetic operators, relational operators, logical operators, assignment operators, augmented assignment operators, identity operators (is, is not), membership operators (in not in) 

● Expressions, statement, type conversion, and input/output: precedence of operators, expression, evaluation of an expression, type-conversion (explicit and implicit conversion), accepting data as input from the console and displaying output. 

● Errors- syntax errors, logical errors, and run-time errors 

● Flow of Control: introduction, use of indentation, sequential flow, conditional and iterative flow ● Conditional statements: if, if-else, if-elif-else, flowcharts, simple programs: e.g.: absolute value, sort numbers and divisibility of a number. 

● Iterative Statement: for loop, range(), while loop, flowcharts, break and continue statements, nested loops, suggested programs: generating pattern, summation of series, finding the factorial of a positive number, etc. 

● Strings: introduction, string operations (concatenation, repetition, membership and slicing), traversing a string using loops, built-in functions/methods–len(), capitalize(), title(), lower(), upper(), count(), find(), index(), endswith(), startswith(), isalnum(), isalpha(), isdigit(), islower(), isupper(), isspace(),lstrip(), rstrip(), strip(), replace(), join(), partition(), split() 

● Lists: introduction, indexing, list operations (concatenation, repetition, membership and slicing), traversing a list using loops, built-in functions/methods– len(), list(), append(), extend(), insert(), count(), index(), remove(), pop(), reverse(), sort(), sorted(), min(), max(), sum(); nested lists, suggested programs: finding the maximum, minimum, mean of numeric values stored in a list; linear search on list of numbers and counting the frequency of elements in a list. 

● Tuples: introduction, indexing, tuple operations (concatenation, repetition, membership and slicing); built-in functions/methods – len(), tuple(), count(), index(), sorted(), min(), max(), sum(); tuple assignment, nested tuple; suggested programs: finding the minimum, maximum, mean of values stored in a tuple; linear search on a tuple of numbers, counting the frequency of elements in a tuple. 

● Dictionary: introduction, accessing items in a dictionary using keys, mutability of a dictionary (adding a new term, modifying an existing item), traversing a dictionary, built-in functions/methods – len(), dict(), keys(), values(), items(), get(), update(), del, clear(), fromkeys(), copy(), pop(), popitem(), setdefault(), max(), min(), sorted(); Suggested programs: count the number of times a character appears in a given string using a dictionary, create a dictionary with names of employees, their salary and access them. 

● Introduction to Python modules: Importing module using ‘import ’ and using from statement, importing math module (pi, e, sqrt(), ceil(), floor(), pow(), fabs(), sin(), cos(), tan()); random module (random(), randint(), randrange()), statistics module (mean(), median(), mode()). 

Unit 3: Society, Law and Ethics 

● Digital Footprints 

● Digital Society and Netizen: net etiquettes, communication etiquettes, social media etiquettes ● Data Protection: Intellectual property rights (copyright, patent, trademark), violation of IPR (plagiarism, copyright infringement, trademark infringement), open source software and licensing (Creative Commons, GPL and Apache) 

● Cyber Crime: definition, hacking, eavesdropping, phishing and fraud emails, ransomware, cyber trolls, cyber bullying 

● Cyber safety: safely browsing the web, identity protection, confidentiality 

● Malware: viruses, trojans, adware 

● E-waste management: proper disposal of used electronic gadgets. 

● Information Technology Act (IT Act) 

● Technology and society: Gender and disability issues while teaching and using computers

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