JNTUK R23 B.Tech IT IV Year I Semester (4-1) Syllabus & Subject-wise Topics

Internet of Things

covers the sensing, connectivity, and processing building blocks that let embedded devices communicate and act autonomously, from low-level protocols up to fog computing and real-world IoT case studies.

• Unit 1: Predecessors and emergence of IoT — WSNs, M2M communication, and IoT networking components
• Unit 2: Sensing and actuation — sensor/actuator characteristics and IoT processing topologies
• Unit 3: Connectivity technologies — Zigbee, RFID, NFC, LoRa, Wi-Fi, and Bluetooth
• Unit 4: Interoperability and fog computing — IoT standards and fog computing architecture
• Unit 5: Paradigms and challenges — emerging IoT trends and agricultural/vehicular IoT case studies

Human Resources & Project Management

combines HR management fundamentals (recruitment, training, performance appraisal) with project management essentials (planning, scheduling, monitoring), preparing students for the managerial dimension of engineering careers.

• Unit 1: HRM fundamentals — HR functions, planning, recruitment, and selection
• Unit 2: HR development — training methods, performance appraisal, and career development
• Unit 3: Project management basics — project life cycle, proposals, and project appraisal
• Unit 4: Project types — management challenges specific to different project categories
• Unit 5: Project implementation and review — project control, human aspects, and performance evaluation

Software Architecture & Design Pattern

(Professional Elective-IV) — teaches reusable object-oriented design patterns and architectural styles (like MVC) for structuring complex, maintainable software systems.

• Unit 1: Introduction to design patterns — the pattern catalog and pattern selection
• Unit 2: System analysis — gathering requirements and defining conceptual classes
• Unit 3: Structural design patterns — adapter, bridge, composite, decorator, facade, and proxy
• Unit 4: MVC architecture — applying MVC to interactive system design
• Unit 5: Distributed objects — Java RMI, web services (SOAP/REST), and enterprise service buses

Deep Learning

(Professional Elective-IV) — covers neural network fundamentals through convolutional and recurrent architectures, building the foundation for modern computer vision and NLP applications.

• Unit 1: Fundamentals of deep learning — evolution of machine learning and overfitting/underfitting
• Unit 2: Introducing deep learning — biological vs. machine vision and training deep networks
• Unit 3: Neural networks — Keras/TensorFlow basics and binary/multiclass classification
• Unit 4: Convolutional and recurrent networks — CNN representation learning and RNNs in PyTorch
• Unit 5: Applications and research — GANs, deep reinforcement learning, and autoencoders

Computer Vision

(Professional Elective-IV) — covers how machines interpret images, from camera models and filtering through segmentation and multi-view geometry, for applications like object recognition and robotic perception.

• Unit 1: Cameras and radiometry — pinhole cameras, shading models, and color perception
• Unit 2: Linear filters and texture — convolution, edge detection, and texture analysis
• Unit 3: Multiple-view geometry — stereopsis and segmentation by clustering
• Unit 4: Model fitting — the Hough transform and Kalman filter-based tracking
• Unit 5: Geometric camera models — camera calibration and model-based vision

Blockchain Technology

(Professional Elective-IV) — covers blockchain fundamentals, consensus mechanisms, and smart contracts across public, private, and consortium blockchain systems, plus their security and application landscape.

• Unit 1: Blockchain fundamentals — consensus mechanisms and cryptocurrency basics
• Unit 2: Public blockchain systems — Bitcoin/Ethereum and smart contracts
• Unit 3: Private and consortium blockchains — Hyperledger, Multichain, and initial coin offerings
• Unit 4: Blockchain security — security challenges and applications in banking, healthcare, and supply chain
• Unit 5: Case studies and implementation — blockchain platforms using Python and Hyperledger Fabric

Agile Methodologies

(Professional Elective-V) — covers the Agile Manifesto, Scrum, XP, and Lean/Kanban practices that shape how modern software teams plan and deliver iteratively.

• Unit 1: Learning agile — the Agile Manifesto and understanding agile values
• Unit 2: Agile principles — the 12 principles and project delivery practices
• Unit 3: Scrum — self-organizing teams, sprints, and scrum planning
• Unit 4: Extreme Programming — XP practices and embracing change through simplicity
• Unit 5: Lean and Kanban — eliminating waste and agile coaching

Big Data Analytics

(Professional Elective-V) — covers the tools and techniques (Hadoop, NoSQL, Spark) used to store, process, and analyze datasets too large for traditional systems.

• Unit 1: Big data landscape — industry examples and Hadoop-based technologies
• Unit 2: NoSQL — aggregate data models, sharding, replication, and Cassandra
• Unit 3: Hadoop ecosystem — HDFS architecture, MapReduce, and Hive
• Unit 4: Apache Spark — RDDs, data frames, and the Catalyst optimizer
• Unit 5: Stream processing — event-time processing and structured streaming

Mobile Computing

(Professional Elective-V) — covers mobile communication standards, network architectures (GSM through 5G/6G), and mobile application infrastructure like synchronization and mobile IP.

• Unit 1: Mobile communications overview — signal propagation and mobile computing architecture
• Unit 2: 2G/3G/4G architectures — GSM services, GPRS, and wireless communication standards
• Unit 3: Mobile IP — packet delivery, handover management, and MANET/WSN basics
• Unit 4: Synchronization — mobile agents and data synchronization strategies
• Unit 5: Short-range networks — WLAN architecture and the wireless application protocol

Cyber Physical Systems

(Professional Elective-V) — covers the integration of computation with physical processes, including synthesis, security, synchronization, and real-time scheduling of CPS.

• Unit 1: Symbolic synthesis — construction of symbolic models for CPS
• Unit 2: CPS security — cyber security requirements and attack models
• Unit 3: Synchronization — distributed consensus algorithms and time-triggered architecture
• Unit 4: Real-time scheduling — fixed timing parameters and multicore scheduling
• Unit 5: Model integration — semantic domains for time and CPS modeling languages

Quantum Science and Technology

(Open Elective-IV option) — introduces quantum mechanics fundamentals and their application to quantum computing, communication, and sensing technologies emerging as a new computing paradigm.

• Unit 1: Fundamentals of quantum mechanics — the Schrödinger equation and quantum measurement theory
• Unit 2: Quantum information theory — qubits, entanglement, Bell states, and quantum gates
• Unit 3: Quantum computing — Grover’s and Shor’s algorithms and quantum error correction
• Unit 4: Quantum communication — quantum key distribution (BB84, E91) and quantum teleportation
• Unit 5: Quantum technologies — quantum sensors, hardware platforms, and global research initiatives

Open Elective-III / Open Elective-IV

the IT department’s own open-elective offering list pairs Open Elective-III with Object Oriented Programming Through Java (mirroring the II-I core course) and Open Elective-IV with Principles of Software Engineering / Computer Networks / Quantum Science and Technology (Principles of Software Engineering and Computer Networks mirror the II-II and III-I core courses respectively; Quantum Science and Technology is summarized above with its own full syllabus). As with earlier semesters, IT students’ actual Open Elective picks may instead be drawn from another department’s own offering, which this IT syllabus document does not include.

Prompt Engineering

a skill-enhancement course teaching how to design, refine, and evaluate prompts for large language models, from basic prompt anatomy through retrieval-augmented generation and agentic/multimodal applications.

• Foundations of prompt engineering — prompt anatomy, iterative refinement, and diagnosing prompt failures
• Advanced prompt patterns — few-shot prompting, role-based prompting, and constraint specification
• Structured outputs and reasoning — JSON/YAML generation and chain-of-thought prompting
• Retrieval-augmented generation — building LangChain-based RAG pipelines with vector stores
• Agents and multimodal AI — LLM agents, multimodal prompting, and prompt-injection/ethics evaluation

Constitution of India

an audit course covering the structure, rights, and governance mechanisms of the Indian Constitution, building civic literacy alongside the technical curriculum.

• Unit 1: History of the Indian Constitution — the drafting committee and constitutional philosophy
• Unit 2: Constitutional rights and duties — fundamental rights and directive principles
• Unit 3: Organs of governance — Parliament, the executive, and the judiciary
• Unit 4: Local administration — municipalities and Panchayati Raj institutions
• Unit 5: Election Commission — its role, functioning, and welfare bodies for SC/ST/OBC and women