IGNOU MCSL 228 SOLVED ASSIGNMENT
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MCSL 228: AI and Machine Learning Lab
| Title Name | IGNOU MCSL 228 SOLVED ASSIGNMENT |
|---|---|
| Type | Soft Copy (E-Assignment) .pdf |
| University | IGNOU |
| Degree | MASTER DEGREE PROGRAMMES |
| Course Code | MCA-NEW |
| Course Name | Master of Computer Application |
| Subject Code | MCSL 228 |
| Subject Name | AI and Machine Learning Lab |
| Year | 2025 |
| Session | - |
| Language | English Medium |
| Assignment Code | MCSL 228/Assignment-1/2025 |
| Product Description | Assignment of MCA-NEW (Master of Computer Application) 2025. Latest MCSL 228 2026 Solved Assignment Solutions |
| Last Date of IGNOU Assignment Submission | Last Date of Submission of IGNOU BEGC-131 (BAG) 2025-26 Assignment is for January 2026 Session: 30th September, 2026 (for December 2025 Term End Exam). Semester Wise January 2025 Session: 30th March, 2026 (for June 2026 Term End Exam). July 2025 Session: 30th September, 2025 (for December 2025 Term End Exam). |
| Format | Ready-to-Print PDF (.soft copy) |
📅 Important Submission Dates
- January 2025 Session: 31st October, 2025
- July 2025 Session: 30th April, 2025
Why Choose Our Solved Assignments?
• Guidelines: Strictly follows 2025-26 official word limits.
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📋 Assignment Content Preview
MCSL 228 (January 2025 - July 2025) - ENGLISH
Course Code : MCSL-228
Course Title : AI and Machine Learning Lab
Assignment Number : MCA_NEW(III)/L-228/Assign/2025
Maximum Marks : 100
Weightage : 30%
Last Dates for Submission : 30th April, 2025 (for January session)
31st October, 2025 (for July session)
This assignment has 8 Questions for 40 marks. Answer all the questions. Your Lab Record will carry 40 Marks. Rest 20 marks are for viva voce. You may use illustrations and diagrams to enhance the explanation. Please go through the guidelines regarding assignments given in the programme guide for the format of presentation.
Note: You must execute the program and submit the program logic, sample input and output along with the necessary documentation. Assumptions can be made wherever necessary.
Q1: Write a Python Program to implement Breadth First Search.
Q2: Write a Python Program to implement Min-Max Algorithm.
Q3: Write a Python Program to implement the Backtracking approach to solve N Queen's problem
Q4: Write a Python Program to implement A* Algorithm.
Q5: Write a Python Program to implement Naïve Bayes Algorithm for data classification, choose dataset of your own choice.
Q6: Write a Python Program to implement Polynomial Regression on a dataset of your own choice.
Q7: Take a Data set as per your choice, implement and execute on different inputs of K-Means clustering algorithm.
Q8: Write a Python Program to implement FP tree growth Algorithm on a dataset of your own choice.
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