Comprehensive Course Structure
| Semester | Course Code | Course Title | Credit (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| 1 | IT-101 | Engineering Mathematics I | 4-0-0-4 | None |
| 1 | IT-102 | Physics for Information Technology | 3-0-0-3 | None |
| 1 | IT-103 | Chemistry for Computer Applications | 3-0-0-3 | None |
| 1 | IT-104 | Computer Fundamentals and Programming | 3-0-2-5 | None |
| 1 | IT-105 | Introduction to IT Lab | 0-0-2-2 | None |
| 1 | IT-106 | English for Communication Skills | 3-0-0-3 | None |
| 2 | IT-201 | Engineering Mathematics II | 4-0-0-4 | IT-101 |
| 2 | IT-202 | Data Structures and Algorithms | 3-0-2-5 | IT-104 |
| 2 | IT-203 | Database Management Systems | 3-0-2-5 | IT-202 |
| 2 | IT-204 | Operating Systems | 3-0-2-5 | IT-104 |
| 2 | IT-205 | Computer Networks | 3-0-2-5 | IT-104 |
| 2 | IT-206 | Software Engineering | 3-0-2-5 | IT-202 |
| 3 | IT-301 | Design and Analysis of Algorithms | 3-0-2-5 | IT-202 |
| 3 | IT-302 | Machine Learning Fundamentals | 3-0-2-5 | IT-201, IT-202 |
| 3 | IT-303 | Cybersecurity Principles | 3-0-2-5 | IT-204, IT-205 |
| 3 | IT-304 | Cloud Computing Architecture | 3-0-2-5 | IT-205 |
| 3 | IT-305 | Data Analytics and Visualization | 3-0-2-5 | IT-201, IT-202 |
| 3 | IT-306 | Internet of Things (IoT) Engineering | 3-0-2-5 | IT-205 |
| 4 | IT-401 | Advanced Machine Learning | 3-0-2-5 | IT-302 |
| 4 | IT-402 | Blockchain Technology | 3-0-2-5 | IT-303 |
| 4 | IT-403 | DevOps and Continuous Integration | 3-0-2-5 | IT-204 |
| 4 | IT-404 | Human-Computer Interaction | 3-0-2-5 | IT-206 |
| 4 | IT-405 | Mobile Application Development | 3-0-2-5 | IT-202 |
| 4 | IT-406 | Research Methodology | 2-0-0-2 | IT-301 |
Detailed Departmental Elective Courses
The Information Technology program at Itm Skills University Navi Mumbai offers advanced departmental electives designed to deepen specialization and foster innovation. These courses are carefully selected to ensure alignment with industry trends and academic excellence.
Advanced Machine Learning (IT-401)
This course delves into the mathematical foundations of machine learning algorithms, including neural networks, deep learning architectures, reinforcement learning, and unsupervised learning techniques. Students will implement complex models using Python libraries such as TensorFlow and PyTorch. The course emphasizes practical applications in natural language processing, computer vision, and robotics.
Learning Objectives:
- Understand advanced neural network architectures
- Implement reinforcement learning algorithms
- Apply deep learning techniques to real-world problems
- Evaluate model performance using appropriate metrics
Blockchain Technology (IT-402)
This course explores the technical foundations of blockchain systems, including distributed consensus mechanisms, smart contracts, cryptographic protocols, and decentralized applications. Students will develop practical skills in Ethereum development, Solidity programming, and blockchain network architecture.
Learning Objectives:
- Design secure blockchain systems
- Develop smart contracts using Solidity
- Understand cryptocurrency protocols
- Evaluate blockchain scalability solutions
DevOps and Continuous Integration (IT-403)
This course covers modern DevOps practices including containerization with Docker, orchestration with Kubernetes, CI/CD pipeline implementation, infrastructure as code, and cloud deployment strategies. Students will gain hands-on experience with tools such as Jenkins, GitLab CI, and AWS.
Learning Objectives:
- Implement automated testing frameworks
- Design scalable deployment pipelines
- Manage infrastructure using configuration management tools
- Optimize application performance in cloud environments
Human-Computer Interaction (IT-404)
This course focuses on designing user-centered interfaces and evaluating usability in digital systems. Students will study cognitive psychology, interaction design principles, prototyping techniques, and accessibility standards. The course includes practical projects involving user research, wireframing, and iterative design processes.
Learning Objectives:
- Apply UX design principles to interface development
- Conduct usability studies and analyze user feedback
- Create interactive prototypes using design tools
- Evaluate accessibility compliance with international standards
Mobile Application Development (IT-405)
This course provides comprehensive training in mobile app development for both iOS and Android platforms. Students will learn native development frameworks, cross-platform solutions, API integration, and mobile UI/UX design principles.
Learning Objectives:
- Build responsive mobile applications
- Integrate third-party APIs and services
- Implement offline functionality and data synchronization
- Evaluate app performance and security measures
Project-Based Learning Philosophy
The Information Technology program at Itm Skills University Navi Mumbai embraces a project-based learning approach that integrates theoretical knowledge with practical implementation. This methodology ensures students develop real-world problem-solving skills while working on meaningful challenges.
Mini-Projects Structure
Mini-projects are mandatory components throughout the program, starting from the second year and continuing until the final year. These projects are designed to reinforce learning outcomes and provide opportunities for hands-on experience.
- First-year mini-project: Simple web application development using HTML/CSS/JavaScript
- Second-year mini-project: Database-driven application with backend integration
- Third-year mini-project: Team-based solution addressing a real-world challenge
Each mini-project follows a structured evaluation process involving:
- Technical documentation and code quality
- Presentation and demonstration skills
- Peer review and feedback mechanisms
- Faculty evaluation based on project outcomes
Final-Year Thesis/Capstone Project
The capstone project represents the culmination of the student's academic journey, requiring them to integrate knowledge from all disciplines studied. Students work under the guidance of faculty mentors to develop innovative solutions addressing contemporary technological challenges.
Project selection process:
- Faculty mentorship availability and research interests
- Student preferences and career aspirations
- Industry relevance and potential impact
- Resource availability and feasibility constraints
Evaluation criteria include:
- Innovation and originality of approach
- Technical execution and quality
- Documentation and presentation skills
- Impact assessment and potential for commercialization