# CBSE Class-12 Syllabus 2019-20 (Computer Science)

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## CBSE Class-12 Syllabus 2019-20 (Computer Science)

Computer Science(New)
CLASS-XII
Code No. 083

Optional for the academic year 2019-20 and mandatory for the academic year 2020-21 onwards
1. Prerequisites
Computer Science- Class XI
2. Learning Outcomes

1. Understand the concept of functions and recursion.
2. Learn how to create and use Python libraries.
3. Learn file handling.
4. Learn about the concept of efficiency in algorithms and computing in general.
5. Learn basic data structures: lists, stacks, and queues.
6. Get a basic understanding of computer networks: network stack, basic network hardware, basic protocols, and basic tools.
7. Connect a Python program with an SQL database, and learn aggregation functions in SQL.
8. Have a clear understanding of cyber ethics and cybercrime. Understand the value of technology in societies, gender and disability issues, and the technology behind biometric ids.

3. Distribution of Marks

 Unit No. Unit Name Marks 1. Programming and Computational Thinking – 2 30 2. Computer Networks 15 3. Data Management – 2 15 4. Society, Law and Ethics – 2 10 5. Practicals 30 Total 100

4.1 Unit 1: Programming and Computational Thinking (PCT-2) (80 Theory + 70 Practical)

• Revision of the basics of Python
• Functions: scope, parameter passing, mutable/immutable properties of data objects, pass arrays to functions, return values, functions using libraries: mathematical, and string functions.
• File handling: open and close a file, read, write, and append to a file, standard input, output, and error streams, relative and absolute paths.
• Using Python libraries: create and import Python libraries
• Recursion: simple algorithms with recursion: factorial, Fibonacci numbers; recursion on arrays: binary search
• Idea of efficiency: performance defined as inversely proportional to the wall clock time, count the number of operations a piece of code is performing, and measure the time taken by a program. Example: take two different programs for the same problem, and understand how the efficient one takes less time.
• Data visualization using Pyplot: line chart, pie chart, and bar chart.
• Data-structures: lists, stacks, queues.