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    Scholarships & exams

    support@collegese.com
    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Information Technology

    School of Computer Application, Sri Satya Sai University of Technology and Medical Sciences
    Duration
    4 Years
    Information Technology UG OFFLINE

    Duration

    4 Years

    Information Technology

    School of Computer Application, Sri Satya Sai University of Technology and Medical Sciences
    Duration
    Apply

    Fees

    ₹8,50,000

    Placement

    92.0%

    Avg Package

    ₹65,00,000

    Highest Package

    ₹1,20,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Information Technology
    UG
    OFFLINE

    Fees

    ₹8,50,000

    Placement

    92.0%

    Avg Package

    ₹65,00,000

    Highest Package

    ₹1,20,00,000

    Seats

    300

    Students

    1,200

    ApplyCollege

    Seats

    300

    Students

    1,200

    Curriculum

    Comprehensive Course Listing Across 8 Semesters

    Semester Course Code Course Title Credit Structure (L-T-P-C) Prerequisites
    1 IT101 Engineering Mathematics I 3-1-0-4 None
    1 IT102 Physics for Information Technology 3-1-0-4 None
    1 IT103 Introduction to Programming 2-0-2-4 None
    1 IT104 English for Communication 3-0-0-3 None
    1 IT105 Computer Organization & Architecture 3-1-0-4 None
    2 IT201 Engineering Mathematics II 3-1-0-4 IT101
    2 IT202 Electronic Devices & Circuits 3-1-0-4 IT102
    2 IT203 Data Structures and Algorithms 3-1-0-4 IT103
    2 IT204 Database Management Systems 3-1-0-4 IT103
    2 IT205 Operating Systems 3-1-0-4 IT105
    3 IT301 Probability and Statistics 3-1-0-4 IT201
    3 IT302 Object-Oriented Programming with Java 2-0-2-4 IT203
    3 IT303 Computer Networks 3-1-0-4 IT205
    3 IT304 Web Technologies and Development 3-1-0-4 IT204
    3 IT305 Software Engineering 3-1-0-4 IT203
    4 IT401 Design and Analysis of Algorithms 3-1-0-4 IT301
    4 IT402 Digital Signal Processing 3-1-0-4 IT301
    4 IT403 Advanced Database Systems 3-1-0-4 IT204
    4 IT404 Compiler Design 3-1-0-4 IT303
    4 IT405 Human Computer Interaction 3-1-0-4 IT203
    5 IT501 Machine Learning 3-1-0-4 IT401
    5 IT502 Cryptography and Network Security 3-1-0-4 IT303
    5 IT503 Data Mining and Analytics 3-1-0-4 IT301
    5 IT504 Cloud Computing 3-1-0-4 IT303
    5 IT505 Internet of Things 3-1-0-4 IT205
    6 IT601 Artificial Intelligence 3-1-0-4 IT501
    6 IT602 Big Data Technologies 3-1-0-4 IT503
    6 IT603 Software Testing and Quality Assurance 3-1-0-4 IT305
    6 IT604 Mobile Application Development 3-1-0-4 IT404
    6 IT605 Information System Design 3-1-0-4 IT305
    7 IT701 Research Methodology 2-0-2-4 IT501
    7 IT702 Capstone Project I 0-0-6-6 IT501, IT601
    7 IT703 Advanced Topics in IT 3-1-0-4 IT601
    7 IT704 Professional Ethics and Legal Issues 2-0-0-2 None
    8 IT801 Capstone Project II 0-0-6-6 IT702
    8 IT802 Entrepreneurship and Innovation 2-0-2-4 IT703
    8 IT803 Internship 0-0-0-12 IT702

    Detailed Descriptions of Advanced Departmental Electives

    These advanced elective courses are designed to deepen students' understanding of specialized areas within Information Technology, preparing them for leadership roles in industry and academia.

    Machine Learning (IT501)

    This course introduces students to fundamental concepts in machine learning including supervised and unsupervised learning algorithms, neural networks, deep learning architectures, and reinforcement learning. Students gain hands-on experience using libraries like TensorFlow and PyTorch, developing projects that apply these techniques to real-world datasets.

    Cryptography and Network Security (IT502)

    Students explore cryptographic protocols, secure communication systems, and network defense mechanisms. Topics include symmetric and asymmetric encryption, digital signatures, PKI infrastructure, intrusion detection systems, and compliance frameworks such as ISO 27001.

    Data Mining and Analytics (IT503)

    This course covers data preprocessing, clustering, classification, association rule mining, anomaly detection, and visualization techniques. Students work with large datasets using tools like Python Scikit-learn, R, and Apache Spark to extract meaningful insights.

    Cloud Computing (IT504)

    Students learn about cloud infrastructure models, service models, virtualization technologies, containerization platforms, and orchestration tools. Practical labs involve deploying applications on AWS, Azure, and Google Cloud Platform environments.

    Internet of Things (IT505)

    This course explores IoT architectures, sensor networks, embedded systems programming, edge computing, and smart city applications. Labs include building physical prototypes using Raspberry Pi and Arduino microcontrollers connected to cloud services.

    Artificial Intelligence (IT601)

    Advanced topics in AI including knowledge representation, planning, reasoning under uncertainty, natural language processing, robotics, and computer vision. Students implement intelligent agents and develop applications using modern AI frameworks.

    Big Data Technologies (IT602)

    This course delves into Hadoop ecosystem, Spark SQL, streaming analytics, NoSQL databases, and data warehousing concepts. Students design scalable big data solutions for enterprise environments.

    Software Testing and Quality Assurance (IT603)

    Students study software testing methodologies, automation tools, quality metrics, risk analysis, and compliance standards. Practical sessions involve designing test cases, executing automated tests, and reporting defects in real-world projects.

    Mobile Application Development (IT604)

    This elective focuses on cross-platform mobile app development using Flutter, React Native, and native frameworks for iOS and Android. Students build fully functional apps integrated with backend services.

    Information System Design (IT605)

    The course emphasizes system analysis and design principles, UML modeling, database design, and enterprise architecture patterns. Students create comprehensive information systems for business scenarios using agile methodologies.

    Project-Based Learning Philosophy

    The department believes that effective learning occurs through active engagement with real-world challenges. Project-based learning forms the backbone of our curriculum, encouraging students to collaborate, innovate, and solve complex problems.

    Mini-projects are introduced in early semesters, allowing students to experiment with concepts learned in class. These projects are typically completed within 4-6 weeks and evaluated based on creativity, technical execution, and teamwork.

    The final-year thesis or capstone project spans the entire academic year. Students select a topic aligned with their interests and career goals, working closely with faculty mentors who guide them through research methodologies, literature review, experimentation, and documentation processes.

    Project selection involves a proposal submission phase where students present their ideas to the faculty committee for approval. Evaluation criteria include originality, feasibility, impact potential, and alignment with departmental strengths and industry trends.