Class 12 Artificial Intelligence Practical Examination Question Paper Set 1 with Answer Key (CBSE – 843)
Preparing for the CBSE Class 12 Artificial Intelligence (Subject Code 843) Practical Examination?
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We are providing Class 12 AI Practical Examination Question Paper – Set 1, 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 1
| www.anjeevsinghacademy.com | ||
| All India Senior Secondary Certificate Examination School Code: xxxxx [SET – 1] | ||
| Time 3 Hours | Subject: Artificial Intelligence (843) | M.M.: 50 | ||
| Q. No. | Questions | Marks |
| 1. | LAB TEST | 10 |
| A | Write a python program to create a dataframe containing the following records. (6) Note: Name is index and subject is the columns in the dataframe. Write the command to perform the following task. Display all indexDisplay the dimensions of the dataframeAdd one row for Naveen with all subject marks.Add one more subject SST with all students’ marks. Remove subject English. | |
| B | Explore the Iris Flower dimensions with Orange Data Mining tools and visualize the data with a scatter plot. Note: write down all the steps in the answer sheet. (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 1 with Answer Key
| www.anjeevsinghacademy.com | ||
| All India Senior Secondary Certificate Examination School Code: xxxxx [SET – 1] | ||
| Time 3 Hours | Subject: Artificial Intelligence (843) | M.M.: 50 | ||
| Q. No. | Questions | Marks |
| 1. | LAB TEST | 10 |
| A | Write a python program to create a dataframe containing the following records. (6) Note: Name is index and subject is the columns in the dataframe. Write the command to perform the following task. a. Display all index b. Display the dimensions of the dataframe c. Add one row for Naveen with all subject marks. d. Add one more subject SST with all students’ marks. e. Remove subject English. | |
| Ans | import pandas as pd import numpy as np # Creating the DataFrame data = { “Maths”: [90, 91, 97, 89, 65, 93], “Science”: [92, 81, np.nan, 87, 50, 88], “English”: [89, 91, 88, 78, 77, 82], “Hindi”: [81, 71, 67, 82, np.nan, 89], “AI”: [94, 95, 99, np.nan, 96, 99] } names = [“Heena”, “Shefali”, “Meera”, “Joseph”, “Suhana”, “Bismeet”] df = pd.DataFrame(data, index=names) print(df) # a. Display all index print(df.index) # b. Display the dimensions of the DataFrame print(df.shape) # c. Add one row for Naveen with all subject marks df.loc[“Naveen”] = [88, 85, 90, 86, 92] print(df) # d. Add one more subject SST with all students’ marks df[“SST”] = [75, 80, 78, 82, 70, 85, 88] print(df) # e. Remove subject English df.drop(“English”, axis=1, inplace=True) print(df) | |
| B | Explore the Iris Flower dimensions with Orange Data Mining tools and visualize the data with a scatter plot. Note: write down all the steps in the answer sheet. (4) | |
| Ans | Steps: 1. Open the Orange Data Mining application on the computer. 2. Drag and drop the File widget from the Data section onto the workflow area. 3. Double-click the File widget and select the built-in dataset Iris. 4. Drag the Scatter Plot widget from the Visualize section. 5. Connect the File widget to the Scatter Plot widget. 6. Open the Scatter Plot widget. 7. Select any two attributes (for example, Petal Length on X-axis and Petal Width on Y-axis). 8. Set the Color option to Iris Species to differentiate flower types. 9. Observe the distribution and relationship of Iris flower dimensions in the scatter plot. | |
| 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 1 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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