B.Sc. (Information Technology) Artificial Intelligence Application Development and Jira Syllabus - Mumbai University 2026

This is the TY BSc IT syllabus under NEP 2020, in force from the academic year 2026-27. The University still sets the earlier Choice Based papers alongside it for ATKT candidates, so check which scheme your exam form names before you revise.

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Syllabus for Artificial Intelligence Application Development and Jira

Major · Semester 5 · TY BSc IT · 2 credits · 50 marks

Module I: Introduction to AI and Intelligent Agents

1. Design a Simple Rational Agent by defining PEAS for Vacuum Cleaner Environment and Autonomous Taxi. Classify environments (fully/partially observable, deterministic/stochastic, episodic/sequential). Implement a simple table-driven agent in Python. Problem Solving by Searching (Uninformed Search) 2. Given an initial configuration of the 8-puzzle and a goal configuration, write a Python program to find the shortest sequence of moves to reach the goal state using Breadth-First Search (BFS). 3. Given two water jugs of 4 litres and 3 litres capacity, write a Python program to obtain exactly 2 litres in one jug using Depth-First Search (DFS). [Vary capacity of jugs] Given a weighted graph representing cities and distances between them, write a Python program to find the least-cost path from Arad to Bucharest using Uniform Cost Search (UCS). [Provide any other weighted graph for applying UCS] Problem Solving by Searching (Informed Search) 1. Given an initial configuration of the 8-puzzle and a goal configuration, write a Python program to find the solution using Greedy Best-First Search with the Manhattan Distance heuristic. 2. Given an initial configuration of the 8-puzzle and a goal configuration, write a Python program to find the shortest path using A* search with the Manhattan Distance heuristic. 3. Given a weighted graph representing cities and distances between them, write a Python program to find the shortest path from Arad to Bucharest using A* search with a heuristic function (straight-line distance to destination). Bayes’ Rule Application 1. Scenario: A medical test is used to detect a particular disease. The probability that a randomly selected person has the disease is 1%. If a person has the disease, the test returns positive with probability 99%. If a person does not have the disease, the test still returns positive with probability 5% (false positive rate). A person takes the test and receives a positive result. Problem Statement: Write a Python program to compute the probability that the person actually has the disease given that the test result is positive. Naïve Bayes’ Classification 1. Using a small dataset (e.g., weather or spam dataset), implement a Naive Bayes classifier using scikit-learn. Probability Reasoning (Bayesian Networks & Inference) 1. Using a simple example (Burglary–Alarm), create a Bayesian Network using pgmpy. 2. Write a program to compute Posterior Probability using Bayesian Networks(Burglar|Alarm = True) Machine Learning 1. Using any small dataset (e.g., Iris or a CSV dataset), write a Python program to demonstrate the basic machine learning workflow.
a Load dataset using Pandas.
b Perform basic preprocessing (handling missing values or scaling).
c Split dataset into training and testing sets.
d Train a simple classifier.
e Display training and testing accuracy. 2. Using a suitable regression dataset, implement Linear Regression using scikit- learn. 3. Using the MNIST dataset (digit vs not digit), implement a binary classifier. 4. Implement k-fold cross-validation on a classification model. 5. Implement a Decision Tree classifier using the Iris or any relevant dataset. 6. Implement Decision Tree regression on a regression dataset. 7. Implement k-Nearest Neighbors (kNN) classifier. 8. Implement multiclass classification using Logistic Regression or Decision Tree. Ethics and Bias Analysis Select any publicly available dataset (for example, Iris, Adult Income, or a classification dataset of your choice) and analyze it for possible bias and class imbalance.

Module II: Jira Setup & Project Configuration, Advanced Configuration,

Reporting & Governance Practical 1: Jira Setup & Project Creation A. Create a Jira Cloud account and explore the dashboard. B. Create a Company-managed Scrum/Kanban Project. C. Configure project details Practical 2: Team Creation & Role Assignment A. Add Team Members B. Assign Roles Practical 3: Issue Types & Configuration A. Create and configure Issue Types (Epic, Story, Task, Bug) B. Create Components and Versions. Practical 4: Issue Management A. Create issues under an Epic. B. Assign issues to users and set Priority & Due Date. Practical 5: Workflow Customization A. Design a custom workflow B. Add transitions and conditions. C. Publish and associate workflow with a project. Practical 6: Scrum Board & Sprint Management A. Create and configure Scrum Board. B. Create and start a Sprint. C. Complete Sprint and generate Sprint Report Practical 7: Kanban Board Management A. Create a Company-managed Kanban Project. B. Configure Kanban Board C. Track issue progress and generate Control Chart Practical 8: JQL & Filters A. Write basic JQL queries (Status, Assignee, Priority). B. Create and save filters. Practical 9: Reports & Dashboards A. Generate Burndown Chart and Velocity Chart. B. Create Pie Chart / Issue Statistics Report. C. Create a Custom Dashboard with gadgets. Practical 10: Permission & Security Management A. View and modify Project Permission Scheme. B. Configure Project Roles and assign permissions. Practical 11: Jira Automation A. Create an Automation Rule (Trigger → Condition → Action). B. Configure rule (e.g., When issue is moved to Done → send email / auto-assign). C. Test and enable automation rule. Practical 12: Introduction to Jira Mobile App A. Install and configure the Jira Mobile App. B. View and update issues from mobile (Status, Comment, Assign). Receive notifications and manage real-time updates
a https://artint.info/3e/slides/index.html
b https://soclibrary.futa.edu.ng/books/Machine%20Learning%20Engine ering%20(Andriy%20Burkov)%20(Z-Library).pdf 5. Highsmith, Jim. Agile Project Management: Creating Innovative Products. Addison-Wesley. 6. Cohn, Mike. Succeeding with Agile: Software Development Using Scrum. Addison-Wesley. 7. Rubin, Kenneth S. Essential Scrum: A Practical Guide to the Most Popular Agile Process. Addison-Wesley. 8. https://www.atlassian.com/software/jira/guides 9. JIRA 4.3 Documentation User documentation for JIRA Software Server 7.1

Text Books

1 Artificial Intelligence: A Modern Approach – Stuart Russell and Peter Norvig – Pearson Education, 2020
2 Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow – Aurélien Géron,O’Reilly Media, 2022 (Third Edition)
3 Schwaber, Ken & Sutherland, Jeff. The Scrum Guide.
4 Official Documentation of Jira Software by Atlassian.
1 The Hundred-Page Machine Learning Book – Andriy Burkov – Andriy Burkov, 2020 (First Edition)
2 Machine Learning for Absolute Beginners – Oliver Theobald – Independently published, 2020 (First Edition)
3 Artificial Intelligence: Foundations of Computational Agents – David L. Poole and Alan K. Mackworth – Cambridge University Press, 2023 (Third Edition)
a https://artint.info/3e/slides/index.html
b https://soclibrary.futa.edu.ng/books/Machine%20Learning%20Engine ering%20(Andriy%20Burkov)%20(Z-Library).pdf
5 Highsmith, Jim. Agile Project Management: Creating Innovative Products. Addison-Wesley.
6 Cohn, Mike. Succeeding with Agile: Software Development Using Scrum. Addison-Wesley.
7 Rubin, Kenneth S. Essential Scrum: A Practical Guide to the Most Popular Agile Process. Addison-Wesley.
8 https://www.atlassian.com/software/jira/guides
9 JIRA 4.3 Documentation User documentation for JIRA Software Server 7.1

Reproduced from the University of Mumbai syllabus for B.Sc. (Information Technology) under NEP 2020, in force from the academic year 2026-27. Wording is as printed in that syllabus. Module numbering is as printed there too.

The complete syllabus

This subject is cut from the University circular for its year. Open a document here if you want the whole thing rather than a single subject.

PDF BSc IT SEM I & II (2024 25) NEP NEP 2020 syllabus, in force from 2024-25 Read full PDF Read

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