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Fees
₹2,50,000
Placement
92.5%
Avg Package
₹65,00,000
Highest Package
₹1,40,00,000
Fees
₹2,50,000
Placement
92.5%
Avg Package
₹65,00,000
Highest Package
₹1,40,00,000
Seats
300
Students
1,200
Seats
300
Students
1,200
The Information Technology program at SHA SHIB COLLEGE OF TECHNOLOGY is structured over 8 semesters, combining core academic subjects with practical lab work and specialized electives. The curriculum is designed to provide students with a strong foundation in computer science principles while enabling them to specialize in areas of interest.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | IT101 | Introduction to Programming | 3-0-0-3 | None |
| 1 | IT102 | Mathematics for IT | 4-0-0-4 | None |
| 1 | IT103 | Computer Organization and Architecture | 3-0-0-3 | None |
| 1 | IT104 | Physics for IT | 3-0-0-3 | None |
| 2 | IT201 | Data Structures and Algorithms | 4-0-0-4 | IT101 |
| 2 | IT202 | Operating Systems | 3-0-0-3 | IT103 |
| 2 | IT203 | Database Management Systems | 3-0-0-3 | IT101 |
| 2 | IT204 | Web Technologies | 3-0-0-3 | IT101 |
| 3 | IT301 | Computer Networks | 3-0-0-3 | IT202 |
| 3 | IT302 | Software Engineering | 3-0-0-3 | IT201 |
| 3 | IT303 | Object-Oriented Programming with Java | 3-0-0-3 | IT101 |
| 3 | IT304 | Discrete Mathematics | 3-0-0-3 | IT102 |
| 4 | IT401 | Advanced Algorithms | 3-0-0-3 | IT201 |
| 4 | IT402 | Machine Learning | 3-0-0-3 | IT201 |
| 4 | IT403 | Cloud Computing | 3-0-0-3 | IT201 |
| 4 | IT404 | Data Analytics and Visualization | 3-0-0-3 | IT201 |
| 5 | IT501 | Cybersecurity Fundamentals | 3-0-0-3 | IT301 |
| 5 | IT502 | Internet of Things (IoT) | 3-0-0-3 | IT301 |
| 5 | IT503 | Human-Computer Interaction | 3-0-0-3 | IT201 |
| 5 | IT504 | DevOps and CI/CD | 3-0-0-3 | IT201 |
| 6 | IT601 | Advanced Data Science | 3-0-0-3 | IT404 |
| 6 | IT602 | Big Data Technologies | 3-0-0-3 | IT404 |
| 6 | IT603 | Blockchain and Cryptocurrency | 3-0-0-3 | IT201 |
| 6 | IT604 | Mobile Application Development | 3-0-0-3 | IT201 |
| 7 | IT701 | Research Methodology | 3-0-0-3 | None |
| 7 | IT702 | Project Planning and Management | 3-0-0-3 | IT302 |
| 7 | IT703 | Specialized Elective I | 3-0-0-3 | Depends on Track |
| 7 | IT704 | Specialized Elective II | 3-0-0-3 | Depends on Track |
| 8 | IT801 | Final Year Project | 6-0-0-6 | IT701, IT702 |
| 8 | IT802 | Internship | 6-0-0-6 | IT701, IT702 |
The Information Technology program offers a wide range of advanced departmental electives designed to deepen students' knowledge in specialized areas. Here are descriptions of ten such courses:
This course introduces students to the fundamentals of machine learning and deep neural networks, covering supervised and unsupervised learning algorithms, regression models, clustering techniques, and convolutional and recurrent neural networks. Students will implement models using Python libraries like TensorFlow and PyTorch, gaining hands-on experience in building predictive systems for real-world applications.
This course explores modern cybersecurity threats, defense mechanisms, and secure system design principles. Topics include encryption standards, firewalls, intrusion detection systems, penetration testing, and risk assessment methodologies. Students will participate in hands-on labs simulating real-world attacks and defensive strategies.
Focused on cloud platforms such as AWS, Azure, and Google Cloud, this course covers infrastructure as code (IaC), containerization with Docker, orchestration with Kubernetes, CI/CD pipelines, microservices architecture, and scalable deployment strategies. Students will gain practical experience deploying applications in production environments.
This course equips students with tools and techniques for analyzing large datasets using technologies like Hadoop, Spark, Python (Pandas, NumPy), SQL, and visualization libraries like Tableau or Plotly. Emphasis is placed on statistical modeling, data mining, feature engineering, and extracting actionable insights from complex datasets.
This course focuses on software development lifecycle, agile methodologies, system design principles, API design, database normalization, testing frameworks (JUnit, Selenium), and enterprise-level application architecture. Students will work on full-stack projects to understand end-to-end software development processes.
This course explores IoT device development, sensor integration, wireless communication protocols (WiFi, Bluetooth, Zigbee), embedded programming with C/C++, real-time operating systems, and smart city applications. Students will build prototype IoT systems using Raspberry Pi and Arduino platforms.
This course delves into user-centered design principles, usability testing, interaction design patterns, prototyping tools (Figma, Sketch), accessibility standards, and cognitive psychology in UI/UX design. Students will conduct user research, create wireframes, and prototype interfaces for various digital products.
This course encourages innovation through ideation, business model creation, lean startup methodologies, pitch deck development, and venture capital funding. Students will work in teams to develop innovative solutions and present their ideas to industry experts and investors.
This advanced elective covers NoSQL databases, distributed systems, data warehousing, OLAP vs OLTP, indexing strategies, transaction management, and database security. Students will design and optimize complex database schemas for large-scale applications.
This course introduces quantum mechanics, quantum algorithms (Shor’s algorithm, Grover’s search), quantum cryptography, and post-quantum cryptography. It explores how quantum computing may revolutionize security and computation in the future.
SHA SHIB COLLEGE OF TECHNOLOGY emphasizes project-based learning as a core pedagogical approach to ensure that students gain practical skills and real-world experience. This methodology encourages collaborative work, critical thinking, and problem-solving in multidisciplinary contexts.
The program includes mandatory mini-projects during the second and third years, followed by a comprehensive final-year thesis or capstone project. Mini-projects typically span 2–3 months and involve working in teams of 4–6 students on specific technological challenges. These projects are supervised by faculty mentors and evaluated based on innovation, technical execution, presentation quality, and impact.
The final-year capstone project is a substantial endeavor that spans the entire semester. Students select a research topic or industry problem relevant to their specialization track. They work closely with a faculty advisor and often collaborate with external partners such as startups or corporations. The project culminates in a written report, oral defense, and demonstration of a working prototype or solution.
Project selection is guided by student interests, faculty expertise, and industry relevance. Faculty mentors are chosen based on their research background, availability, and alignment with the project scope. Students may also propose independent projects after consultation with department heads.
Evaluation criteria for all projects include technical depth, clarity of presentation, adherence to deadlines, collaboration skills, documentation quality, and ethical considerations in technology development.
