Class 12 Artificial Intelligence Practical Examination Question Paper Set 2 with Answer Key (CBSE – 843)
Preparing for the CBSE Class 12 Artificial Intelligence (Subject Code 843) Practical Examination?
You’re at the right place.
We are providing Class 12 AI Practical Examination Question Paper – Set 2, along with its complete Answer Key, strictly designed as per the latest CBSE practical exam pattern.
This resource is extremely useful for students, teachers, and schools for:
- Board practical exam preparation
- Pre-board practical assessments
- Lab practice and revision
- Internal practical evaluation
📘 Practical Question Paper Set 2
| www.anjeevsinghacademy.com | ||
| All India Senior Secondary Certificate Examination School Code: xxxxx [SET – 2] | ||
| Time 3 Hours | Subject: Artificial Intelligence (843) | M.M.: 50 | ||
| Q. No. | Questions | Marks |
| 1. | LAB TEST | 10 |
| A | Write a Python program to train and evaluate a classification model. (6) | |
| B | Perform NLP or Computer Vision using Orange. (4) | |
| 2 | Capstone Project | 15 |
| 3 | Project Documentation | 6 |
| 4 | Video | 4 |
| 5 | Practical File | 10 |
| 6 | Viva Voce | 5 |
| External Examiner Internal Examiner Name : ____________ Name : ______________ Sign : ____________ Sign : _______________ Examiner No: _________ Examiner No: ___________ | ||
📘 Practical Question Paper Set 2 with Answer Key
| www.anjeevsinghacademy.com | ||
| All India Senior Secondary Certificate Examination School Code: xxxxx [SET – 2] | ||
| Time 3 Hours | Subject: Artificial Intelligence (843) | M.M.: 50 | ||
| Q. No. | Questions | Marks |
| 1. | LAB TEST | 10 |
| A | Write a Python program to train and evaluate a classification model. (6) | |
| Ans | import pandas as pd from sklearn.model_selection import train_test_split from sklearn.linear_model import LogisticRegression from sklearn.metrics import accuracy_score, confusion_matrix # Sample dataset data = { “Hours”: [2, 4, 6, 8, 10], “Result”: [0, 0, 1, 1, 1] } df = pd.DataFrame(data) X = df[[“Hours”]] y = df[“Result”] # Split data X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2) # Model model = LogisticRegression() model.fit(X_train, y_train) # Prediction y_pred = model.predict(X_test) # Evaluation print(“Accuracy:”, accuracy_score(y_test, y_pred)) print(“Confusion Matrix:\n”, confusion_matrix(y_test, y_pred)) | |
| B | Perform NLP or Computer Vision using Orange. (4) | |
| Ans | NLP Steps: Load text dataset using Corpus widget Apply Preprocess Text Use Sentiment Analysis widget Analyze positive and negative sentiments Computer Vision Steps: Load image dataset Apply Image Embedding Connect Classification widget Evaluate using Test & Score | |
| 2 | Capstone Project | 15 |
| 3 | Project Documentation | 6 |
| 4 | Video | 4 |
| 5 | Practical File | 10 |
| 6 | Viva Voce | 5 |
🎯 Syllabus Coverage
Python
- NumPy and Pandas
- DataFrames and CSV files
- Handling missing values
- Model evaluation
- TensorFlow regression model
Orange Data Mining
- Data visualization (Scatter Plot, Box Plot)
- Feature selection using Rank widget
- Classification using Random Forest
- Model evaluation using Test & Score
- Introductory NLP / Computer Vision concepts
👨🏫 Who Should Use This Paper?
✔ Class 12 AI Students (CBSE Board)
✔ Artificial Intelligence Teachers
✔ Computer Science / AI Departments
✔ Schools conducting practical exams
📥 Download Section
👉 Download: Class 12 Artificial Intelligence Practical Examination Paper Set 2 with Answer Key (PDF)
📌 Note
Students are advised to practice this paper in exam conditions to improve confidence and time management.
Teachers may use this paper for practice tests, revision labs, or mock practical exams.
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