West Bengal WBCHSE Class 12 Applied Artificial Intelligence (APAI) Syllabus 2024-25: Download PDF

Unit

Sub

Topic

Marks

Unit-1

Different Types of Data & Various Application Areas of AI (5)

1a

● Structured data

● unstructured (Audio, video, and text) data

● semi-structured data

2

1b

● Natural Language Processing

● speech recognition

● Computer vision

● weather Predictions

● Self-driving cars

● Autonomous systems

● robotics

(A brief description of each area, focusing on the question: what is it?)

3

Unit -2 

AI in Natural Language Processing (10)

2

● Definition of Natural language processing (NLP)

● Applications of NLP

●  Major Natural Language Processing applications- Chatbots,

● Autocomplete in Search Engines

● Voice Assistants (Siri, Alexa, or Google Assistant),

● Machine translation

● Grammar Checkers, Email Classification and Filtering,

● Sentiment analysis, Fake news detection, hate speech detection.

(Brief explanation of each NLP topic using suitable examples. Roles of AI and ML in the respective application (brief explanation in storytelling fashion with a suitable diagram only . Sophisticated math must be avoided).

● Use cases: Sentiment analysis, common features extraction using NLTK toolkit (Bag-of-words model, TF-IDF features, n-gram features), classification tools - KNN model, Decision Tree, ANN (in Scikit learn) training sentiment analysis model and testing the learned model (Use block diagram and ML tools, no mathematical description or derivation ).

10

Unit -3

AI in Speech Recognition (7)

3

What is a speech signal? Applications of Speech recognition. How does it differ from text.? Common audio format(.wav,.mp3), description of basic speech features(Frequency, Amplitude, pitch, zero crossing rate, energy, and autocorrelation, MFCC), feature extraction using Python toolbox (no mathematics, only concepts), speech recognition using ANN(in Scikit learn). Roles of AI and ML in speech recognition.

7

Unit -4

AI in Image Processing & Computer Vision (8)

4

What is computer vision? Applications of Image Analysis and Computer Vision. Common image and video formats (very brief description .jpeg, .tiff, .bmp,.mp4,.avi), Color Model: RGB, image representation in computer, image binarization(Threshold Based) , image features-pixel features, Gray Scale Values as Features, Mean pixel values of channels, Edge features(Prewitt kernel, Sobel kernel,), Texture Feature, Use case: image classification using the Animal dataset(three classes- dogs, cats, and pandas) , image representation with examples, description of the Animal dataset, Using ML tools like k-NN or others for classification (A brief description of the steps: Data collection, Data representation, Split the Dataset into train and test sets, Train the Classifier, Evaluation using Scikit learn tools).

8

Unit -5

AI for Weather Predictions (5)

Problem definition, Features, Time series data (stock market time series analysis ), ARIMA Model (briefly) Data representation, Prediction using linear regression (using regression tools, no mathematical derivation).

5

Unit

Sub

Topic

Marks

 Unit -6

AI for Medicine and Health care (7)

6

How is AI Changing Medical Science (brief notes). AI for medical disease detection using- Diabetes detection using Machine Learning Algorithm (KNN, ANN), AI for medical diagnostic-disease detection using computer vision (Example-based), AI for Medical Prognosis(example-based). AI for health surveillance (sensor-based examples with flow diagram). Will Clinicians be replaced by AI? Limitations and Challenges in the Application of Artificially Intelligent Systems in Medical Science (Discussion on each topic should be brief and be example-based).

7

 Unit -7.

AI for Business (6)

7a

AI for Economics:

How can AI reshape the future of economics? AI-powered economic forecasting, Stock market prediction, Regression-based Forecasting of economic indicators such as GDP and inflation, a brief description of each use case, and block diagram architecture of the AI model used for forecasting. Challenges and limitations of using AI for economic forecasting

3

7b

AI for eCommerce:

How is AI changing eCommerce? Recommendation System Steps (Collecting user data, Analyzing data, Filtering, Generating recommendations). Recommendation using user-based k-nearest neighbors, Online shopping, virtual assistants, chatbots, and voice assistants (Brief introduction to each use case).

3

Unit -8

AI for Government Law and Policy-making (3)

8

● Introduction, AI tool-based analysis of the reactions of the common people when a new policy is to be introduced.

● Automatic legal advisers, AI-based methods for legal document retrieval and processing for supporting argumentation (example-based).

3

Unit -9.

AI in Environment Sustainability (5)

9

What is meant by environmental sustainability? GreenHouse Effect Carbon Footprint. Renewable energy forecasting using machine learning (Regression Based ). How can AI help in environment sustainability (brief description with suitable examples).

5

Unit -10.

Chatbots, Large Language Models, and ChatGPT (7)

10

How does a chatbot work? A block-level diagram for a chatbot. What is a language model? How does the traditional language model differ from a Large Language Model? What is chatGPT? How is it related to deep learning? How does it function? Impact of chatGPT on various sectors like education, health, etc. What is Prompt Engineering? What is its importance?

7

 Unit -11

Benefits, Risks and Ethics of AI (7)

11

● Positive aspects of AI, negative aspects of AI.

● Short notes on various risks of the misuse of AI- Lethal autonomous weapons, surveillance, and persuasion, biased decision-making, impact on employment, safety-critical applications, and cyber security (example-based discussion).

● AI ethics - Commonly cited principles to be followed while creating or using AI technology, the ethical side of lethal autonomous weapons, Surveillance, security, privacy, fairness and bias, trust and transparency, and robot rights (each topic should be discussed in brief with suitable examples).

7

WBCHSE Class 12 Health And Physical Education Syllabus 2024-25 PDF

Project 

10 Marks

Viva

05 Marks

Practical Exam

15 Marks

Total

30 Marks

Suggested Experiments (at least 3 Experiments must be Completed)

1.  Develop a machine learning-based sentiment analysis model (Python-based Scikit Learn tools)

2. a) Write a Python Program to read a .wav audio file and visualize the signal

b) Develop spoken numeral recognition using MFCC features and KNN (Python-based Scikit Learn tools) .

3. a) Write a Python Program to read an image and display the image.

a) Develop an image classification system using ANN on Animal dataset (Python-based Scikit Learn tools)

4. Develop a simple weather prediction system using a regression tool (Python-based Scikit Learn tools).

5. Develop a Diabetes prediction system using ANN (Python-based Scikit Learn tools)

6. Develop a chatbot using existing tools

7. Use chatGPT for various tasks: Writing Essay, Letters, Poem, Coding Assistant, Compose song lyrics, Generate Movie Scripts,

1

Fundamentals of computers, E Balagurusamy, McGraw Hill,2009

2

Artificial Intelligence: A modern approach, Stuart Russell, Peter Norvig, Pearson Edition

3

Principles of Artificial Intelligence, Nills J. Nilsson, Springer Berlin, Heidelberg

4

Machine Learning by Peter Flach, Cambridge University Press

5

Machine Learning, Tom Mitchell, McGraw Hill, 1997

6

Introduction to Machine Learning with Python by Andreas C Muller, Sarah Guido, Publisher(s): O’Reilly Media