Semester 7 Syllabus & Notes

This subject develops practical skills in automated testing of Android mobile applications using Appium, including emulator and real-device setup, Appium Inspector, and native app automation. It also covers Agile and Scrum practices, defect management with Jira and Bugzilla, and mobile testing tools such as Katalon Studio, Espresso, Robotium, and Selendroid.

This subject covers conventional and modern cryptography, symmetric-key and public-key algorithms, hashing, digital signatures, key distribution, and security mechanisms across TCP/IP layers. It also examines attacks on wireless ad hoc networks and applies cryptographic techniques through practical programming exercises.

This course covers advanced Java programming, including collections streams, lambda operations, GUI and event handling, JDBC database applications, file I/O, JSP, date/time APIs, localization, multithreading, and concurrency. Students develop Java applications, connect applications to databases using JDBC, and use lambda expressions and concurrency features.

This course covers 3D game development in Unity, including 3D modelling, procedural environments, player controls, AI-driven behaviours, advanced scripting, lighting, user interfaces, immersive experiences, storytelling, multiplayer development and optimization.

The course covers blockchain fundamentals, decentralization, symmetric and public-key cryptography, consensus algorithms, Bitcoin networks and transactions, alternative coins, smart contracts, Ethereum, Geth, Web3, and decentralized applications. It also includes practical work involving Solidity, MetaMask, Remix IDE, contract deployment, and Ethereum account and genesis-block management using Geth.

This course covers the design and development of intelligent, autonomous, conversational, and multi-agent AI systems using Azure AI Foundry, Python, Semantic Kernel, AutoGen, and Azure AI services. It also addresses workflow automation, testing, monitoring, deployment, responsible AI, security, governance, and enterprise applications.

This course develops students' ability to navigate and manage Linux environments, administer files, users, permissions, processes, services, networking, packages, storage, security, and system logs. It also covers SSH, scheduled tasks, SELinux, logical volumes, ACLs, NFS, boot management, installation, troubleshooting, and automation using Red Hat Enterprise Linux.

This course provides an overview of NoSQL databases and MongoDB fundamentals for handling scalable, schema-flexible data. Students learn data modeling, CRUD operations, indexing, aggregation, application integration, AI-based predictive analytics, and development of a functional mini-project.

This course develops skills in designing Raspberry Pi-based IoT systems, including GPIO and peripheral control, sensor interfacing, serial communication, computer vision, and cloud-edge integration. Students implement practical smart systems using communication protocols, cloud platforms, data processing, and embedded hardware.

This course introduces key terms associated with contemporary drama and examines socio-political issues, thematic concerns, stylistic and narrative techniques, motifs, and symbols in selected literary works. The prescribed works include Top Girls, Mother Courage and Her Children, Final Solutions, A Streetcar Named Desire, and The Piano Lesson.

This subject develops the fashion design process through user-centered briefs, research, trend forecasting, ideation, historical and cultural analysis, and design development. Students create and evaluate fashion concepts, materials, collections, design documentation, rendered presentations, and a professional digital portfolio.

This course develops skills in malware analysis and cyber defence through static and dynamic analysis, assembly and disassembly, malicious binary debugging, malware persistence, code injection, hooking, and obfuscation techniques. It also covers memory forensics, advanced malware detection, malware hunting, and defence strategies.

This course develops skills in building web applications with Python and Django, including project and app structure, views, URL mapping, templates, forms, models, migrations, ORM, and Django Admin. It also covers cookies, sessions, authentication, user management, permissions, testing, debugging, and database configuration.

Cluster Computing covers Apache Spark and Scala for distributed data processing, including RDDs, Spark SQL, GraphX, Spark Streaming with Apache Kafka, and machine learning using Spark MLlib and PySpark. The course emphasizes applying these technologies to big-data processing, analytics, graph processing, and practical machine-learning workflows.

This subject covers cloud security principles and practices, including identity and access management, secure networking, compute and storage security, security operations, backup and recovery, vulnerability assessment, and emerging cloud security trends. It emphasizes practical security configuration using Microsoft Azure and related cloud technologies.

This course develops foundational and practical skills in iPhone application programming using Swift and Xcode. It covers Swift programming concepts, MVVM architecture, UIKit controls, TableViews, iPhone project templates, responsive layouts, databases, multimedia, MapKit, WKWebView, and web-service integration.

This course develops proficiency in C# and ASP.NET Core for building MVC applications and RESTful Web APIs. It covers object-oriented programming, Razor views, model binding and validation, middleware, dependency injection, authentication and authorization, Entity Framework Core, SQL Server, CRUD operations, and API testing with Postman.

This course covers software project management, including project planning, cost and effort estimation, software development life cycle models, risk management, resource allocation, monitoring and control, and software quality management. It also includes AI-assisted estimation and monitoring, Agile, DevOps, CI/CD, earned value analysis, and blockchain-based traceability.

This laboratory course develops practical software project management skills using tools such as Microsoft Project, GitHub, Asana, and Jira. It covers project planning, task and resource management, Gantt and PERT charts, network diagrams, cost management, progress tracking, collaborative planning, and Agile project execution.

This course develops skills in building and optimizing deep learning models using TensorFlow and Keras. It covers NVIDIA DGX Station A100, convolutional and recurrent neural networks, autoencoders, generative adversarial networks, and model deployment using Docker and Streamlit.