Page 12 - Touhpad Ai

Planning/Writing Session
The candidates will be required to prepare an algorithm and a handwritten program to solve the problem.

Examination Session
The program handed in at the end of the Planning/Writing session shall be returned to the candidates. The candidates will
be required to do and execute the program individually on the computer, hardware and show execution to the examiner.
A printout of the program listing, including output should be attached to the answer script containing the handwritten
program and hardware results. This should be returned to the examiner. The program should be sufficiently documented
so that the material required, circuit diagram/block diagram, algorithm, representation and development process is clear
from reading the program. Large differences between the planned program and the printout will result in loss of marks.

Teachers should maintain a record of all the assignments done as part of the practical work throughout the year and give
it due credit at the time of cumulative evaluation at the end of the year. Students are expected to do a minimum of twenty
assignments for the year and ONE project based on the syllabus.

LIST OF SUGGESTED ASSIGNMENTS:
1. How would you use Matplotlib to create a line plot for visualizing the trend of a dataset over time? Write a Python
program demonstrating this.
2. Using Seaborn, how can you create a scatter plot to analyze the relationship between two variables in a dataset?
Provide a Python program illustrating this.

3. Explain how to utilize Matplotlib to generate a bar plot for comparing the distribution of categories in a dataset.
Write a Python program for this purpose

4. Write a Python program demonstrating how to identify outliers in a dataset and handle them using outlier detection
techniques.
5. Describe how to create a box plot using Seaborn to visualize the distribution of a numerical variable. Provide a
Python program to illustrate this.
6. How can you create a pair plot using Seaborn to visualize pairwise relationships between variables in a dataset?
Write a Python program demonstrating this.
7. Write a Python program using NumPy to simulate coin flips and calculate the probability of getting heads.
8. Demonstrate how to generate random samples from a normal distribution using NumPy and visualize the
distribution using Matplotlib. Provide a Python program for this task.
9. Write a Python program to create a Pandas DataFrame from a Kaggle dataset.
10. Perform a hypothesis test to determine if there is a significant difference in temperature between two cities. Write
a Python script to conduct the test and interpret the results.

NOTE: This list is indicative only. Teachers and students should use their imagination to create innovative and original
assignments.

EVALUATION OF PROGRAMMING ASSIGNMENTS
Marks (out of 30) should be distributed as given below.

Continuous Evaluation
Candidates will be required to submit a work file containing the practical work related to assignments done during the year
and ONE project.

Programming assignments done throughout the year 10 marks

Project Work (based on any topic from the syllabus) 5 marks