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B-TECH in Computer Science Engineering Iot Ai at Kalinga Institute of Industrial Technology
Khordha, Odisha
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About the Specialization
What is Computer Science & Engineering (IoT & AI) at Kalinga Institute of Industrial Technology Khordha?
This B.Tech Computer Science & Engineering (IoT & AI) program at Kalinga Institute of Industrial Technology focuses on integrating smart technologies with advanced computational intelligence. It addresses the growing need in the Indian industry for professionals who can develop and manage interconnected devices and intelligent systems. The program differentiates itself by providing a blend of core CSE principles with specialized knowledge in emerging areas of IoT and AI, crucial for India''''s digital transformation.
Who Should Apply?
This program is ideal for fresh graduates seeking entry into cutting-edge technology domains like smart cities, intelligent automation, and data-driven solutions. It also suits working professionals looking to upskill in AI and IoT, and career changers transitioning into the rapidly evolving tech industry. A strong foundation in mathematics and basic programming is a prerequisite for aspiring students.
Why Choose This Course?
Graduates of this program can expect promising India-specific career paths as IoT Architects, AI Engineers, Data Scientists, Embedded Systems Developers, or Machine Learning Specialists. Entry-level salaries typically range from INR 5-8 LPA, with experienced professionals earning INR 15-30+ LPA in Indian companies. The program also aligns with professional certifications from AWS, Google, and NVIDIA, boosting growth trajectories.
Student Success Practices
Foundation Stage
Master Programming Fundamentals & Data Structures- (Semester 1-2)
Consistently practice C/C++ or Python programming and data structures. Focus on logic building, efficient algorithms, and basic problem-solving.
Tools & Resources
HackerRank, LeetCode (easy level), GeeksforGeeks, CodeChef, NPTEL courses on Programming and Data Structures
Career Connection
Strong fundamentals are essential for cracking initial technical rounds in placements and building robust software solutions.
Build a Strong Mathematical Base- (Semester 1-2)
Pay close attention to Engineering Mathematics I & II, especially linear algebra, probability, and statistics. These are critical for understanding AI and Machine Learning concepts.
Tools & Resources
Khan Academy, NPTEL, textbooks, participating in math quiz clubs
Career Connection
A solid mathematical foundation is indispensable for advanced AI/ML roles and research opportunities.
Engage in Peer Learning & Collaborative Projects- (Semester 1-2)
Form study groups, discuss complex topics, and work on small academic projects together. Participate in hackathons or coding challenges.
Tools & Resources
GitHub for version control, Discord/WhatsApp for communication, college project labs
Career Connection
Develops teamwork, communication skills, and practical application of theoretical knowledge, crucial for industry roles.
Intermediate Stage
Deep Dive into AI/ML Concepts with Python- (Semester 3-5)
Go beyond classroom material for Python for ML and Machine Learning. Work on mini-projects using libraries like NumPy, Pandas, Scikit-learn, and start exploring TensorFlow/PyTorch.
Tools & Resources
Kaggle, Coursera (Andrew Ng''''s ML course), Medium articles on ML, Google Colab, GPU access for experiments
Career Connection
Essential for specialized roles in AI/ML, data science, and intelligent system development.
Gain Practical Experience in IoT Prototyping- (Semester 4-5)
Experiment with IoT hardware platforms like Arduino or Raspberry Pi. Build small-scale IoT projects integrating sensors, actuators, and cloud communication.
Tools & Resources
Arduino IDE, Raspberry Pi OS, various sensor modules, AWS IoT Core, Google Cloud IoT Core, Tinkercad (for simulation)
Career Connection
Provides hands-on skills for IoT development, embedded systems, and smart device engineering roles.
Develop Robust Software Engineering Practices- (Semester 4-5)
Apply principles of software engineering in all projects, focusing on design patterns, version control, testing, and documentation. Contribute to open-source projects.
Tools & Resources
Git, GitHub/GitLab, Jira/Trello (for project management), Visual Studio Code
Career Connection
Prepares for industry-standard development workflows, ensuring maintainability and scalability of solutions.
Advanced Stage
Undertake Specialization-Focused Capstone Projects- (Semester 7-8)
Dedicate significant effort to your major projects (Project III & IV) by choosing challenging problems in IoT and AI, aiming for innovative solutions or research contributions.
Tools & Resources
Advanced ML frameworks, specialized IoT kits, access to research papers, faculty mentorship
Career Connection
Creates a strong portfolio for placements, demonstrates problem-solving abilities, and can lead to publications or patent applications.
Pursue Internships and Industry Certifications- (Semester 6-8)
Seek out internships at companies focusing on AI, IoT, or related fields. Pursue industry-recognized certifications (e.g., AWS Certified Machine Learning, Google Cloud IoT Developer).
Tools & Resources
LinkedIn, Internshala, company career pages, online certification platforms (Coursera, edX)
Career Connection
Gain real-world experience, build professional networks, and enhance resume for top placements.
Master Interview Skills and Professional Communication- (Semester 7-8)
Regularly practice technical interview questions, participate in mock interviews, and refine soft skills, including presentation and communication.
Tools & Resources
InterviewBit, LeetCode (medium/hard), company-specific interview guides, Toastmasters, campus placement cell workshops
Career Connection
Crucial for converting technical knowledge into successful job offers and thriving in a professional environment.
Program Structure and Curriculum
Eligibility:
- Passed 10+2 or equivalent examination with at least 60% marks in aggregate with Physics, Chemistry, and Mathematics (PCM) as compulsory subjects. Appeared in KIITEE / JEE (Main).
Duration: 8 semesters / 4 years
Credits: 160 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA1001 | Engineering Mathematics – I | BS | 3 | Differential Calculus, Integral Calculus, Sequences & Series, Multivariable Calculus, Vector Calculus |
| CH1001 | Engineering Chemistry | BS | 3 | Atomic Structure, Chemical Bonding, Thermodynamics, Electrochemistry, Organic Chemistry |
| EE1001 | Basic Electrical Engineering | ES | 3 | DC Circuits, AC Circuits, Transformers, Electrical Machines, Power Systems |
| CS1001 | Programming for Problem Solving | ES | 3 | Programming Fundamentals, Control Structures, Functions, Arrays, Pointers, File I/O |
| HS1001 | English | HS | 2 | Communication Skills, Grammar, Reading Comprehension, Essay Writing, Presentation Skills |
| CH1091 | Engineering Chemistry Lab | BS | 1.5 | Volumetric Analysis, pH Metry, Conductometry, Viscosity Measurement, Spectrophotometry |
| EE1091 | Basic Electrical Engineering Lab | ES | 1.5 | DC Circuit Experiments, AC Circuit Experiments, Transformer Testing, Motor Characteristics |
| CS1091 | Programming for Problem Solving Lab | ES | 1.5 | C Programming Exercises, Conditional Statements, Loops, Functions, Array Operations, String Manipulation |
| ME1091 | Manufacturing Practice | ES | 1.5 | Workshop Safety, Fitting, Carpentry, Welding, Sheet Metal Work, Machining |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MA1002 | Engineering Mathematics – II | BS | 3 | Linear Algebra, Differential Equations, Laplace Transforms, Fourier Series, Probability & Statistics |
| PH1001 | Engineering Physics | BS | 3 | Quantum Mechanics, Solid State Physics, Optics, Electromagnetism, Semiconductor Devices |
| ME1001 | Engineering Mechanics | ES | 3 | Statics, Dynamics, Kinematics, Kinetics, Work-Energy Principles |
| CS1002 | Data Structure | PC | 3 | Arrays, Linked Lists, Stacks, Queues, Trees, Graphs |
| CH1002 | Environmental Science & Engineering | ES | 2 | Ecosystems, Environmental Pollution, Waste Management, Global Environmental Issues, Sustainable Development |
| PH1091 | Engineering Physics Lab | BS | 1.5 | Optics Experiments, Semiconductor Device Characteristics, Magnetic Field Measurements, Error Analysis |
| ME1092 | Engineering Graphics & Design Lab | ES | 1.5 | Orthographic Projections, Isometric Projections, Sectional Views, AutoCAD Basics, Solid Modeling |
| CS1092 | Data Structure Lab | PC | 1.5 | Implementation of Stacks, Queues, Linked Lists, Sorting Algorithms, Tree Traversals |
| NC1001 | Sports, Yoga & Wellness | Non-Credit | 0 | Physical Fitness, Yoga Asanas, Pranayama, Meditation, Sports Activities, Healthy Lifestyle |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS2001 | Discrete Mathematics | PC | 3 | Set Theory, Logic, Relations, Graph Theory, Combinatorics, Algebraic Structures |
| CS2002 | Data Base Management System | PC | 3 | ER Model, Relational Model, SQL, Normalization, Transaction Management, Concurrency Control |
| CS2003 | Object-Oriented Programming | PC | 3 | Classes & Objects, Inheritance, Polymorphism, Abstraction, Encapsulation, Exception Handling |
| CS2092 | Data Base Management System Lab | PC | 1.5 | SQL Queries, Database Design, PL/SQL, Report Generation, Database Connectivity |
| CS2093 | Object-Oriented Programming Lab | PC | 1.5 | C++ / Java Programming, Class Implementation, Inheritance Examples, Polymorphism, File I/O |
| CS2101 | Python for Machine Learning | PC | 3 | Python Fundamentals, Data Structures in Python, NumPy, Pandas, Matplotlib, SciKit-learn basics |
| CS2004 | Data Communication & Networking | PC | 3 | OSI Model, TCP/IP Model, Network Topologies, Data Link Layer, Network Layer, Transport Layer Protocols |
| CS2094 | Data Communication & Networking Lab | PC | 1.5 | Socket Programming, Network Configuration, Packet Analysis, Router Configuration, Client-Server Communication |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS2005 | Design and Analysis of Algorithms | PC | 3 | Algorithm Analysis, Divide and Conquer, Greedy Algorithms, Dynamic Programming, Graph Algorithms, NP-Completeness |
| CS2006 | Operating System | PC | 3 | Process Management, CPU Scheduling, Memory Management, Virtual Memory, File Systems, Deadlocks |
| EC2001 | Microprocessor and Microcontroller | PC | 3 | 8085/8086 Architecture, Assembly Language, Peripherals, Interrupts, Microcontrollers, Embedded Systems |
| CS2095 | Design and Analysis of Algorithms Lab | PC | 1.5 | Implementation of Sorting, Searching, Graph Traversal, Dynamic Programming Algorithms |
| CS2096 | Operating System Lab | PC | 1.5 | Linux Commands, Shell Scripting, Process Management, Thread Synchronization, Memory Allocation |
| CS2102 | Machine Learning | PC | 3 | Supervised Learning, Unsupervised Learning, Regression, Classification, Clustering, Neural Networks |
| CS2007 | Computer Architecture & Organization | PC | 3 | CPU Organization, Instruction Sets, Pipelining, Memory Hierarchy, I/O Organization, Parallel Processing |
| EC2091 | Microprocessor and Microcontroller Lab | PC | 1.5 | 8085/8086 Assembly Programming, Interfacing with Peripherals, Microcontroller Projects, Peripheral Control |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS3001 | Formal Languages and Automata Theory | PC | 3 | Finite Automata, Regular Expressions, Context-Free Grammars, Pushdown Automata, Turing Machines, Undecidability |
| CS3002 | Software Engineering | PC | 3 | Software Life Cycle, Requirements Engineering, Design Principles, Software Testing, Project Management, Agile Development |
| CS3003 | Compiler Design | PC | 3 | Lexical Analysis, Syntax Analysis, Semantic Analysis, Intermediate Code Generation, Code Optimization, Symbol Table |
| CS3092 | Software Engineering Lab | PC | 1.5 | UML Diagrams, Software Requirements Specification, Test Case Design, Version Control (Git) |
| CS3093 | Compiler Design Lab | PC | 1.5 | Lexical Analyzer (Lex), Parser (Yacc/Bison), Intermediate Code Generation, Symbol Table Implementation |
| CS3101 | Internet of Things | PC | 3 | IoT Architecture, Sensors & Actuators, Communication Protocols, IoT Platforms, Data Analytics in IoT, IoT Security |
| CS3102 | Deep Learning | PC | 3 | Neural Networks, Backpropagation, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Deep Learning Frameworks |
| CS3801 | Internship / Project – I | ES | 3 | Problem Identification, Literature Review, Project Planning, Initial Implementation, Technical Documentation |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| CS3004 | Computer Graphics | PC | 3 | Graphics Primitives, 2D/3D Transformations, Viewing, Shading, Illumination Models, Animation |
| CS3005 | Web Technology | PC | 3 | HTML, CSS, JavaScript, DOM, AJAX, Server-Side Scripting, Web Security, Responsive Web Design |
| PE-I | Professional Elective – I | PE | 3 | Natural Language Processing, Big Data Analytics, Cloud Computing |
| OE-I | Open Elective – I | OE | 3 | Digital Marketing, Human Computer Interaction |
| CS3094 | Computer Graphics Lab | PC | 1.5 | OpenGL/DirectX basics, 2D/3D Object Rendering, Transformations, Lighting Models |
| CS3095 | Web Technology Lab | PC | 1.5 | HTML/CSS Design, JavaScript Client-Side Scripting, Responsive Web Design, Database Integration |
| CS3802 | Industrial Training / Project – II | ES | 3 | Industry Exposure, Applied Problem Solving, Team Collaboration, Project Implementation, Technical Report Writing |
| HS3001 | Entrepreneurship | HS | 3 | Entrepreneurial Mindset, Business Plan Development, Startup Funding, Marketing Strategies, Legal Aspects of Business, Innovation |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| EC3002 | Digital Signal Processing | PC | 3 | Discrete-Time Signals, Z-Transform, DFT, FFT, Digital Filter Design (FIR/IIR), DSP Applications |
| PE-II | Professional Elective – II | PE | 3 | Data Mining, Cyber Security, Blockchain Technology |
| OE-II | Open Elective – II | OE | 3 | Principles of Management, Financial Management, Organizational Behavior |
| EC3092 | Digital Signal Processing Lab | PC | 1.5 | MATLAB/Python for DSP, FIR/IIR Filter Implementation, Spectral Analysis, Image Processing Basics |
| CS4101 | Advanced AI for IoT | PC | 3 | Edge AI, Federated Learning, Reinforcement Learning for IoT, Computer Vision for IoT, NLP for IoT |
| CS4102 | IoT Security & Privacy | PC | 3 | IoT Vulnerabilities, Authentication, Authorization, Secure Communication Protocols, Data Privacy in IoT, Blockchain for IoT Security |
| CS4801 | Project – III / Mini Project | PC | 3 | Problem Scoping, System Design, Prototyping, Testing and Debugging, Technical Presentation |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| PE-III | Professional Elective – III | PE | 3 | Mobile Computing, Wireless Sensor Networks, Quantum Computing |
| CS4802 | Comprehensive Viva Voce | PC | 3 | Review of Core CSE Concepts, Specialization Knowledge Assessment, Technical Communication Skills, Problem Solving Abilities |
| CS4803 | Project – IV / Main Project | PC | 6 | Research Methodology, System Design and Architecture, Implementation and Testing, Project Report Writing, Final Presentation and Defense |
