IGNOU MCS-224 Assignment 2026-27
Artificial Intelligence & Machine Learning
Last updated by IGNOU: 29 Jul 2026. Guide written from the official PDF on 28 Oct 2026, 04:25 pm.
| Course code | MCS-224 |
|---|---|
| Course title | Artificial Intelligence & Machine Learning |
| Programme | Master of Science Data Science and Analytics (MSCDSA)MSCDSA, MCA_NEW, MCAOL, MAEC, MSCRWEE |
| School | School of Computer and Information Sciences |
| Assignment code | MSCDSA (II)/224/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, Hindi |
About the MCS-224 assignment
The MCS-224 assignment covers learning methods, artificial intelligence applications, search algorithms, knowledge representation, probability, uncertainty and fuzzy sets. Machine learning topics include ensemble methods, classification, regression, support vectors, neural networks, principal component analysis and association-rule mining.
There are 16 compulsory written questions worth 80 marks, with another 20 marks for a compulsory viva voce. Tasks combine explanations, calculations, diagrams and dataset-based problems. Illustrations and diagrams may support your explanations, and presentation should follow the assignment guidelines in the Programme Guide.
What the assignment asks
| Question | Marks | Topic |
|---|---|---|
| Q1 | 5 | Define learning and distinguish rote learning, instruction-based learning, analogy, induction and deduction. |
| Q2 | 4 | Define artificial intelligence and describe its applications in healthcare and agriculture. |
| Q3 | 4 | Determine a minimum-cost solution path between the supplied start and goal states of an 8-puzzle. |
| Q4 | 5 | Apply breadth-first search to the graph provided in the assignment. |
| Q5 | 4 | Represent a statement about a person, their dog and the dog's behaviour using a semantic network. |
| Q6 | 4 | List outcomes for the stated coin-toss experiment and calculate the requested probabilities and relative frequency of tails. |
| Q7 | 4 | Explain Dempster–Shafer theory through a suitable example. |
| Q8 | 5 | Calculate the specified unions, intersections and complements of three supplied fuzzy sets. |
| Q9 | 4 | Explain ensemble learning and its three main classes of methods. |
| Q10 | 7 | Use Naive Bayes and the supplied dataset to predict the species of a sample with specified attributes. |
| Q11 | 7 | Explain decision trees, construct one using ID3 on the supplied data and classify the given unknown sample. |
| Q12 | 5 | Fit a quadratic regression model to the given observations and predict Y when X equals 9. |
| Q13 | 6 | Plot the two labelled point groups and identify their support vectors and optimal separating line. |
| Q14 | 6 | Calculate both outputs of the illustrated feed-forward neural network for four input patterns using the supplied weights and activation rule. |
| Q15 | 5 | Apply principal component analysis to the supplied two-dimensional observations to calculate the principal component. |
| Q16 | 5 | Explain the Apriori algorithm using a suitable example. |
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 16 written questions.
- Follow the Programme Guide's assignment guidelines for presentation.
- You may include illustrations and diagrams to support your explanations.
- Submit the assignment to the Coordinator of your Study Centre by the applicable deadline.
- Timely assignment submission is required for eligibility to appear in the corresponding term-end examination.
- Attend the compulsory assignment viva voce; submitting the written work without attending the viva results in zero marks and an unsuccessful assignment.
Submission dates: 30 April 2027 (June term-end examination; January 2027 session); 31 October 2026 (December term-end examination; July 2026 session).
Frequently asked questions
What is the MCS-224 assignment code for 2026-27?
The course page prints the assignment code as MSCDSA (II)/224/Assign/2026-27.
What are the submission deadlines for MCS-224?
The deadline is 31 October 2026 for the July 2026 session and December term-end examination, and 30 April 2027 for the January 2027 session and June term-end examination. Dates differ by session.
How are the MCS-224 assignment marks distributed?
The assignment carries 100 marks: 80 for the 16 written questions and 20 for viva voce. Its weightage is 30%.
Are all questions and the viva compulsory?
Yes. All 16 written questions must be answered, and the viva is compulsory. Missing the viva after submitting the assignment results in zero marks and the assignment being treated as unsuccessfully completed.
Where should I submit the MCS-224 assignment?
Submit it to the Coordinator of your Study Centre on or before the applicable deadline.
Which language versions are available for this assignment?
The official listing provides English and Hindi versions.
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
- MCSL-069: Artificial Intelligence & Machine Learning Lab
- 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.