West Bengal Board Class 11 Data Science Syllabus 2024-25: Download Detailed Syllabus In PDF!

UNIT NO.

TOPICS

MARKS

Unit -1 Computer Fundamentals (15)

History of computer, Basic Computer hardware, input and output devices, Basic computer architecture, input-output devices, memory and CPU, networking of machines (overview of LAN, MAN, WAN, Internet, Wifi etc), types of computer (workstation, desktop, Smartphone, Embedded

system, etc.), Overview of Software (system software and application software with examples (mention names only)), Definition of Operating System and functions (mention names of some popular operating systems like Windows, Linux, Android, etc).

5

Bit, Byte and Word, Number System (Base, Binary, Decimal, Octal, Hexadecimal), Conversion of number systems, Boolean logic (Boolean Gates ), Boolean operators (OR, AND and NOT), ASCII code, Concept of Algorithm and Flowchart.

5

Basics of Computer Programming (three levels: high-level language, assembly language, machine language, definition and block diagrams), Overview of Compiler and Interpreter (definition and mention name of major compiled (e.g., C, C++) and interpreted languages (e.g., Python), Overview of procedural and object-oriented programming (key features and just the basic differences, mention names of some popular procedural (e.g., BASIC, FORTRAN, C) and object-oriented programming languages (e.g., C++, Java, Python).

5

Unit -2 Introduction to Python Programming (15)

Basics of Python programming (with a simple 'hello world' program, process of writing a program, running it, and print statement), Concept of class and object, Data-types (integer, float, string), the notion of a variable, Operators (assignment, logical, arithmetic etc.), accepting input from the console, conditional statements (If else and Nested If else ), Collections (List, Tuple, Sets and Dictionary), Loops (For Loop, While Loop & Nested Loops), iterator, string and fundamental string operations (compare, concatenation, sub-string etc.), Function, recursion.

5

Overview of linear and nonlinear data structure (definition, schematic view and difference), array (1D, 2D and its relation with matrix, basic operations: access elements using index, insert, delete, search), stack (concept of LIFO, basic operations: Push, Pop, peek, size), queue (concept of FIFO, basic operations: Enqueue, Dequeue, peek, size), use of List methods in Python for basic operations on array, stack and queue, overview of NumPy library and basic array operations (arrange(), shape(), dim (), type () etc.), binary tree (definition and schematic view only).

6

Linear search and binary search algorithm, sorting algorithm ( bubble sort only)

4

Unit -3 History of AI and Introduction to Linear Algebra (5)

History of AI: Alan Turing and cracking enigma, mark 1 machines, 1956- the birth of the term AI, AI winter of ’70s, expert systems of the 1980s, skipped journey of present-day AI. The distinction between the terms AI,

Pattern recognition and Machine Learning.

(Note: it should be taught as a story more than a flow of information about World War 2, Enigma and Alan Turing, and the birth of modern computers)

2

Basic matrix operations like matrix addition, subtraction, multiplication, transpose of matrix, identity matrix. A brief introduction to vectors, unit vectors, normal vectors, and Euclidean space.

3

1. Computer Fundamentals [ No marks ]

● Visit to Computer Lab and familiarization with computers and peripherals and different networking devices (e.g., modem, switch, router).

● Opening of the CPU box/cabinet and identification of different parts (e.g., Motherboard, CPU/Processor, RAM, Hard Disk, power supply).

no marks ( 6 hours )

2. Introduction to Python Programming [ 10 Marks ]

2a.

● Introduction to installation and running of Python codes with Hello World and simple accessing user inputs from console examples.

● Menu-driven arithmetic calculator

● Simple logical and mathematical programs (e.g., printing patterns, Conversion of binary to decimal and vice versa, computing GCD of two numbers, Finding prime numbers, Generating Fibonacci sequence, Computing factorial –iterative and recursive etc.)

● Finding the max, min, average, sum, and length of a list

● Use of basic string methods like upper(), lower(), count(), find(), join(), replace(), split() etc.

3 Marks

(4 hours)

2b.

● Use of Python List methods for Stack and Queue implementation, for example, append() and pop()

● Use of NumPy array methods: arrange(), shape(), ndim(), size(), add(), subtract(), multiply(), divide(), mat() etc.

● Use of NumPy matrix multiplication methods: dot(), matmul(), multiply() etc.

● Linear search and binary search in an array

● Bubble sort in an array

5 Marks

(4 hours)

2c.

Creating data frame from .csv file, excel sheet, python dictionary, python list, tuple operation on data frame.

2 Marks

(4 hours)

3. Foundation for AI and Data Science [ 5 Marks ]

● Generation of random numbers in Python following a certain distribution and filling up random arrays

● Introduction to matplotlib to plot arrays as histograms

● Computation of mean, median and mode

● Computing CDF from PDF and plotting using matplotlib

● Plotting Gaussian distribution with a given mean and standard deviation

● Plotting mixture of Gaussian distributions

5 Marks

(10 hours)

4. Data Visualization [ 10 marks ]

Using Scipy, OpenCV and NLTK libraries run codes for the following

● Visualization of audio data as spectrogram

● Visualization of image data by zooming into pixels

● Visualization of word histograms

10 Marks

(12 Hours)

5. Database Management [5 marks ]

● Use of MySQL database for Creating tables

● Running retrieval, insertion, deletion and updation queries

5 Marks

(8 hours)