IGNOU MCA-NEW MCSL 229 Cloud and Data Science Lab Solved Assignment ENGLISH

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MCSL 229 (January 2026 - July 2026) - ENGLISH

Course Code

MCSL-229

Course Title

:

Cloud and Data Science Lab

Assignment Number

MCA_NEW(III)/L-229/Assign/2026

Maximum Marks

100

Weightage

:

30%

Last Dates for Submission

30th April, 2026 (for January session) 31st October, 2026 (for July session)

The assignment has two parts, A and B. Answer all the questions. Each part is for 20 marks. The lab records of the Cloud Computing Lab and Data Science Lab carry 20 Marks each. The remaining 20 marks are for viva voce. You may use illustrations, diagrams, and screenshots to enhance the explanations. Please go through the guidelines regarding assignments given in the MCA(New) Programme Guide for the format of the presentation. If any assumptions are made, please state them.

PART-I: Cloud Computing Lab

Q1:

(4+3+3-10 Marks)

(a)

Use Google Docs to create a document containing the guidelines for preparing and submitting the MCS-229 practical assignment. Store it on Google Drive and share it with five friends who can view and comment on the guidelines.

(b) Use Google Sheets to create a spreadsheet containing the cloud storage cost of any four cloud services.

Store this cost as per the following headings:

Cloud Service; Web Address of Service; Space Required in GB; Cost per GB; Storage Cost; Discount,

if any: Net Cost.

You may use the following formulas for making the spreadsheet:

Storage Cost Space Required in GB Cost per GB

Discount is computed as:

If Storage Cost 1,00,000 Discount =0

For Storage Cost >= 1,00,000 but <5,00,000

Discount 10% of Storage Cost

For Storage Cost >= 5,00,000

Discount = 25% of Storage Cost

Net Cost = Storage Cost-Discount 

(c) Use Google Slides and prepare nine slides on the topic "Cloud Deployment Models" (Public, Private, Hybrid, Community) in a group of three students by sharing the Google Slides in your group in edit mode. Every group member should create three slides and contribute to the slides of other group members using the Google Slides.

Q2:Using the AWS Free Tier (trial version), explore Amazon S3 cloud storage and Amazon RDS services.

Q3:Use Google App Engine to write a program that finds the transpose of a given matrix. The program should accept matrix input, transpose it on the server, and display the resulting matrix. Deploy it on the Google Cloud. 

PART-II: Data Science Lab

Q1:The weight of 50 students in the class was measured in Kilograms. The following table shows this data.

Perform the tasks (i) to (iv) using R programming. 

42	45	48	50	47	46	44	49	51	43
52	55	54	53	56	58	57	54	55	52
46	48	49	47	45	44	46	48	50	47
60	62	89	59	58	57	60	61	63	59
50	52	51	49	48	47	50	52	53	51

(i) Find the minimum and maximum weight.

(ii) Find the percentage of students whose weight is between 60 and 70 Kilograms.

(iii) Create and draw a frequency distribution using a relevant graph.

(iv) Find the outlier in the data.

Q2:An agricultural research organisation collected the following data on the quantity of fertiliser used in relation to the crop yield across ten different farms. Use R programming to fit a linear regression line to predict the effect of the use of fertiliser on the yield of the crop. Also, predict the yield of the farm that uses 75 kg of fertiliser per acre of the farm. 

Yeh rahi table format me same data:

No.	Use of Fertiliser (kg/acre)	Yield of Crop (quintals/acre)
1	40	18
2	45	20
3	50	22
4	55	24
5	60	20
6	48	21
7	65	29
8	58	25
9	42	19
10	70	32

 

MCSL 229 (January 2025 - July 2025) - ENGLISH

Course Code : MCSL-229

Course Title : Cloud and Data Science Lab

Assignment Number : MCA_NEW(III)/L-229/Assign/2025

Maximum Marks : 100

Weightage : 30%

Last Dates for Submission : 30th April, 2025 (for January session)

31st October, 2025 (for July session

The assignment has two sections. Answer all the questions. Each section is for 20 marks. The lab record of the Cloud Computing Lab and Data Science lab carries 20 Marks each. The remaining 20 marks are for viva voce. You may use illustrations, diagrams and screenshots to enhance the explanation. Please go through the guidelines regarding assignments given in the MCA(New) Programme Guide for the format of the presentation. If any assumptions are made, please state them.

SECTION-I: Cloud Computing Lab

Q1.(a) Use Google Docs to create a document containing the schedule of MCS-229 practical counselling sessions. Store it on Google Drive and share it with five friends who can view and Comment on it.

(b) Use Google Sheets and create a spreadsheet containing the yearly Salary details of 10 employees of a university under the headings employee name, yearly basic salary, DA percentage, Provident fund deductions, Income Tax deduction, and net salary. You may use the following formulas for making the spreadsheet:

DA amount = DA percentage * yearly basic salary Provident fund = 8% of yearly basic salary Income Tax deduction is computed as: For yearly basic salary < 5,00,000 tax=0 For yearly basic salary >= 5,00,000 but <10,00,000 tax = 20% of (yearly basic salary - 5,00,000) For yearly basic salary >= 10,00,000 tax = 1,00,000+ 30% of (yearly basic salary 10,00,000) Net Salary = yearly basic salary + DA amount - Provident fund - tax

(c) Use Google Slides and prepare nine slides on the topic "Platform as a Service (PaaS)" in a group of three students by sharing the Google Slides in your group in edit mode. Every group member should make three slides each and contribute to the slides of other members of her/his group.

Q2:Explore JustCloud file storage solutions and cloud storage on AWS. Use only the trial versions.

Q3:Use Google App Engine to write a program to multiply two matrices. Deploy it on the Google cloud.

SECTION-II: Data Science Lab

Q1:The height of 50 students of class X was measured in centimeters. The following table shows this data. Perform the tasks (i) to (iv) using R programming.

156	155	163	151	141	160	151	131	170	163
165	160	158	168	158	154	162	166	171	141
161	159	158	156	149	145	168	171	165	145
166	167	169	156	164	146	155	164	168	172
156	163	167	157	155	145	171	164	166	195

 

(i) Find the minimum and maximum height.

(ii) Find the percentage of students whose height is between 160 and 170 Centimeters.

(iii) Create and draw the frequency distribution with the help of a relevant graph.

(iv) Find the outlier of the data

Q2:An organisation collected the following data of its employees: “years in employment” and “employee's salary”. Use R programming to fit a linear regression line to predict the effect of years in employment on the employee’s salary. Also, predict the salary of an employee who is employed for 11 years.

Employee Number	Years in Employment	Employee Monthly salary in thousand Rs
1	10	149
2	8	120
3	12	150
4	7	110
5	6	100
6	5	90
7	9	130
8	8	110
9	3	80
10	4	85

 

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