IGNOU MCSL-069 Assignment 2026-27
Artificial Intelligence & Machine Learning Lab
Last updated by IGNOU: 29 Jul 2026. Guide written from the official PDF on 28 Oct 2026, 04:25 pm.
| Course code | MCSL-069 |
|---|---|
| Course title | Artificial Intelligence & Machine Learning Lab |
| Programme | Master of Science Data Science and Analytics (MSCDSA)MSCDSA |
| School | School of Computer and Information Sciences |
| Assignment code | MSCDSA(II)/L-069/Lab_Assign/2026-27 |
| Session | July 2026 and January 2027 |
| Maximum marks | 100 |
| Weightage | 30% |
| Last date (June exam) | 30 Apr 2027 |
| Last date (December exam) | 31 Oct 2026 |
| Medium | English |
About the MCSL-069 assignment
The MCSL-069 assignment covers Python implementations of artificial intelligence search methods and machine learning classifiers. Tasks include N-Queen, Water Jug, Min-Max, AO*, Naïve Bayes, logistic regression, ID3 decision trees and support vector machines.
All eight questions are compulsory and together carry 40 marks. Lab records carry another 40 marks, while the compulsory viva voce carries 20 marks. Programs must be executed, with their logic, sample inputs, outputs and necessary documentation submitted.
What the assignment asks
| Question | Marks | Topic |
|---|---|---|
| Q1 | 4 | Develop a Python solution to the N-Queen problem without recursion. |
| Q2 | 4 | Implement a Python solution to the Water Jug problem. |
| Q3 | 4 | Implement the Min-Max algorithm in Python. |
| Q4 | 6 | Develop a Python implementation of the AO* algorithm. |
| Q5 | 6 | Explain Naïve Bayes and demonstrate its execution in Python using a dataset you choose. |
| Q6 | 4 | Implement logistic regression in Python to classify data from a dataset of your choice. |
| Q7 | 6 | Use a real-time example to implement ID3 decision tree classification in Python. |
| Q8 | 6 | Implement support vector machines in Python for classification using a dataset you choose. |
This is a summary of each question. Download the official PDF above for the exact questions and word limits.
How to write and submit it
- Answer all eight questions.
- Execute each program and submit its logic, sample input, output and necessary documentation.
- Make assumptions wherever necessary; illustrations and diagrams may be used to support explanations.
- Follow the programme guide's assignment presentation guidelines.
- Submit the assignment to your Study Centre Coordinator by the applicable deadline; timely submission is required for the corresponding term-end examination.
- For the term-end practical examination, meet the minimum attendance requirement as well as the assignment submission requirement.
- Attend the compulsory assignment viva voce; submitting the assignment without attending the viva results in zero marks and unsuccessful completion.
Submission dates: 30 April 2027 (June TEE, January 2027 session); 31 October 2026 (December TEE, July 2026 session).
Frequently asked questions
What is the MCSL-069 assignment code for 2026-27?
The course assignment page gives the code MSCDSA(II)/L-069/Lab_Assign/2026-27.
When is the MCSL-069 assignment due?
The deadline is 31 October 2026 for the July 2026 session and December TEE, and 30 April 2027 for the January 2027 session and June TEE.
How are the MCSL-069 assignment marks divided?
The assignment has 100 marks: 40 for the eight questions, 40 for lab records and 20 for viva voce. Its weightage is 30%.
What must be submitted with the Python programs?
You must execute the programs and submit the program logic, sample inputs, outputs and necessary documentation.
Is the MCSL-069 viva compulsory?
Yes. If you submit the assignment but do not attend the viva voce, the assignment is treated as unsuccessfully completed and receives zero marks.
Where should I submit the MCSL-069 assignment?
Submit it to the Coordinator of your Study Centre on or before the applicable due date.
Other IGNOU MSCDSA assignments
- MCS-061: Mathematical Foundations-I
- MCS-066: Mathematical Foundations for Data Science-II
- MCS-067: Data Wrangling and Visualization
- MCS-068: Predictive Data Analysis
- MCS-207: Database Management Systems
- MCS-224: Artificial Intelligence & Machine Learning
- MCSL-070: Data Analysis Lab
Assignment details and PDFs come from IGNOU's official website; the guide is a summary of the official PDF. Always check the latest instructions and last dates on ignou.ac.in or with your Regional Centre before submitting.