Comprehensive Course Structure
The Bachelor of Information Technology program at Truba College of Science and Technology is designed to provide a balanced mix of theoretical knowledge and practical application. The curriculum spans eight semesters with a carefully curated sequence of core courses, departmental electives, science electives, and laboratory sessions.
Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
---|---|---|---|---|
I | IT101 | Introduction to Programming using Python | 3-0-2-4 | - |
I | IT102 | Mathematics for IT | 3-0-2-4 | - |
I | IT103 | Basic Electronics and Communication | 3-0-2-4 | - |
I | IT104 | Computer Organization and Architecture | 3-0-2-4 | - |
I | IT105 | English for Communication | 2-0-2-3 | - |
I | IT106 | Introduction to Information Technology | 2-0-2-3 | - |
I | IT107 | Lab: Python Programming | 0-0-4-2 | - |
I | IT108 | Lab: Basic Electronics | 0-0-4-2 | - |
II | IT201 | Data Structures and Algorithms | 3-0-2-4 | IT101 |
II | IT202 | Database Management Systems | 3-0-2-4 | IT101 |
II | IT203 | Operating Systems | 3-0-2-4 | IT104 |
II | IT204 | Object-Oriented Programming using Java | 3-0-2-4 | IT101 |
II | IT205 | Mathematics for IT II | 3-0-2-4 | IT102 |
II | IT206 | Lab: Data Structures and Algorithms | 0-0-4-2 | IT201 |
II | IT207 | Lab: Database Management Systems | 0-0-4-2 | IT202 |
II | IT208 | Lab: Java Programming | 0-0-4-2 | IT204 |
III | IT301 | Software Engineering and Project Management | 3-0-2-4 | IT201 |
III | IT302 | Network Fundamentals | 3-0-2-4 | IT103 |
III | IT303 | Web Technologies | 3-0-2-4 | IT204 |
III | IT304 | Computer Graphics and Multimedia | 3-0-2-4 | IT201 |
III | IT305 | Mathematics for IT III | 3-0-2-4 | IT205 |
III | IT306 | Lab: Web Technologies | 0-0-4-2 | IT303 |
III | IT307 | Lab: Computer Graphics | 0-0-4-2 | IT304 |
III | IT308 | Lab: Network Fundamentals | 0-0-4-2 | IT302 |
IV | IT401 | Artificial Intelligence and Machine Learning | 3-0-2-4 | IT201 |
IV | IT402 | Cybersecurity Fundamentals | 3-0-2-4 | IT302 |
IV | IT403 | Data Analytics and Visualization | 3-0-2-4 | IT202 |
IV | IT404 | Cloud Computing Technologies | 3-0-2-4 | IT302 |
IV | IT405 | Internet of Things (IoT) | 3-0-2-4 | IT103 |
IV | IT406 | Lab: AI and ML | 0-0-4-2 | IT401 |
IV | IT407 | Lab: Cybersecurity | 0-0-4-2 | IT402 |
IV | IT408 | Lab: IoT Development | 0-0-4-2 | IT405 |
V | IT501 | Advanced Web Development | 3-0-2-4 | IT303 |
V | IT502 | Mobile Application Development | 3-0-2-4 | IT303 |
V | IT503 | Blockchain and Cryptocurrency | 3-0-2-4 | IT201 |
V | IT504 | DevOps Practices | 3-0-2-4 | IT301 |
V | IT505 | User Experience Design | 3-0-2-4 | IT304 |
V | IT506 | Lab: Mobile App Development | 0-0-4-2 | IT502 |
V | IT507 | Lab: Blockchain Development | 0-0-4-2 | IT503 |
V | IT508 | Lab: DevOps | 0-0-4-2 | IT504 |
VI | IT601 | Capstone Project I | 3-0-2-4 | IT501, IT502 |
VI | IT602 | Research Methodology | 3-0-2-4 | - |
VI | IT603 | Entrepreneurship and Innovation | 2-0-2-3 | - |
VI | IT604 | Professional Ethics and Social Responsibility | 2-0-2-3 | - |
VI | IT605 | Lab: Capstone Project I | 0-0-4-2 | IT601 |
VII | IT701 | Capstone Project II | 3-0-2-4 | IT601 |
VII | IT702 | Internship | 0-0-8-0 | - |
VII | IT703 | Lab: Capstone Project II | 0-0-4-2 | IT701 |
VIII | IT801 | Final Year Thesis | 3-0-2-4 | - |
VIII | IT802 | Lab: Final Year Thesis | 0-0-4-2 | IT801 |
Advanced Departmental Electives
The department offers several advanced departmental electives that allow students to delve deeper into specialized areas of interest. These courses are designed to provide cutting-edge knowledge and practical skills aligned with industry trends.
Advanced Web Development
This course explores modern web frameworks, RESTful APIs, responsive design principles, server-side rendering, and full-stack development techniques. Students learn to build scalable, secure, and performant web applications using technologies like React, Node.js, Express, MongoDB, and GraphQL.
Mobile Application Development
This elective focuses on developing cross-platform mobile apps using Flutter and React Native frameworks. Students gain hands-on experience with mobile UI/UX design, app deployment to app stores, integration with backend services, and performance optimization techniques for iOS and Android platforms.
Blockchain and Cryptocurrency
This course covers blockchain architecture, smart contracts, cryptocurrency fundamentals, consensus mechanisms, decentralized applications (dApps), and regulatory frameworks. Students implement real-world projects using Ethereum, Hyperledger Fabric, and other blockchain platforms while exploring use cases in finance, supply chain, healthcare, and more.
DevOps Practices
This course introduces students to continuous integration/continuous delivery (CI/CD) pipelines, containerization with Docker, orchestration with Kubernetes, infrastructure automation, monitoring tools, and security practices. It emphasizes real-world implementation of DevOps methodologies in agile software development environments.
User Experience Design
This elective teaches the principles of user-centered design, usability testing, prototyping, interaction design, accessibility standards, and design thinking. Students learn to conduct user research, create wireframes and mockups, and evaluate designs using various tools and methodologies.
Artificial Intelligence and Machine Learning
This course covers machine learning algorithms, neural networks, deep learning frameworks, natural language processing, computer vision, reinforcement learning, and ethical considerations in AI. Students implement projects using Python libraries like TensorFlow, PyTorch, scikit-learn, and NLTK.
Cybersecurity Fundamentals
This course explores network security protocols, cryptographic techniques, penetration testing, digital forensics, information security management, and compliance frameworks. Students learn to defend against cyber threats and implement secure system architectures using industry-standard tools and methodologies.
Data Analytics and Visualization
This elective focuses on statistical analysis, data mining, predictive modeling, big data technologies (Hadoop, Spark), visualization tools (Tableau, Power BI), and business intelligence platforms. Students analyze real-world datasets and generate actionable insights for decision-making processes.
Cloud Computing Technologies
This course covers cloud architecture, virtualization, distributed computing, microservices, containerization, cloud security, and multi-cloud strategies. Students deploy applications on AWS, Azure, and Google Cloud Platform while learning about serverless computing, DevOps practices in the cloud, and cost optimization techniques.
Internet of Things (IoT)
This course explores sensor technologies, embedded systems programming, wireless communication protocols, IoT platform development, smart city applications, and edge computing. Students build IoT solutions using Raspberry Pi, Arduino, and other microcontrollers while integrating with cloud services.
Project-Based Learning Philosophy
The department strongly believes in project-based learning as a means to foster critical thinking, problem-solving abilities, and practical skills among students. The approach encourages collaborative work, real-world application of theoretical concepts, and continuous feedback from faculty mentors.
Mini-projects are introduced from the second year onwards, allowing students to apply foundational knowledge in practical scenarios. These projects often involve teamwork, where students take on different roles such as project manager, developer, tester, or designer.
The final-year thesis/capstone project is a comprehensive endeavor that integrates all aspects of the program. Students work closely with faculty mentors and industry partners to develop innovative solutions addressing real-world challenges. The evaluation criteria include technical depth, creativity, documentation quality, presentation skills, and overall impact of the project.
Students can select their projects based on personal interests or collaborate with faculty members working on ongoing research initiatives. Faculty mentors are assigned based on student preferences and the availability of resources in relevant domains. Regular progress meetings and milestone reviews ensure that projects stay on track and meet quality standards.