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    +91 88943 57155
    Pune, Maharashtra, India

    Duration

    4 Years

    Computer Science

    University Of Petroleum And Energy Studies Dehradun
    Duration
    4 Years
    Computer Science UG OFFLINE

    Duration

    4 Years

    Computer Science

    University Of Petroleum And Energy Studies Dehradun
    Duration
    Apply

    Fees

    ₹3,50,000

    Placement

    92.0%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹12,00,000

    OverviewAdmissionsCurriculumFeesPlacements
    4 Years
    Computer Science
    UG
    OFFLINE

    Fees

    ₹3,50,000

    Placement

    92.0%

    Avg Package

    ₹6,50,000

    Highest Package

    ₹12,00,000

    Seats

    120

    Students

    800

    ApplyCollege

    Seats

    120

    Students

    800

    Curriculum

    Comprehensive Course Structure

    The Computer Science program at University of Petroleum and Energy Studies Dehradun is structured over 8 semesters, with a balanced mix of core courses, departmental electives, science electives, and laboratory sessions. The curriculum is designed to provide students with a strong foundation in computer science principles while allowing them to specialize in areas of interest.

    SemesterCourse CodeCourse TitleCredits (L-T-P-C)Prerequisites
    1CS101Introduction to Programming3-0-0-3None
    1CS102Mathematics for Computer Science3-0-0-3None
    1CS103Computer Organization3-0-0-3None
    1CS104Introduction to Data Structures3-0-0-3CS101
    1CS105Lab: Programming and Data Structures0-0-3-0CS101, CS104
    2CS201Data Structures and Algorithms3-0-0-3CS104
    2CS202Object-Oriented Programming3-0-0-3CS101
    2CS203Database Management Systems3-0-0-3CS104
    2CS204Computer Networks3-0-0-3CS103
    2CS205Lab: Data Structures and Algorithms0-0-3-0CS201
    3CS301Software Engineering3-0-0-3CS202
    3CS302Operating Systems3-0-0-3CS103
    3CS303Artificial Intelligence3-0-0-3CS201
    3CS304Cybersecurity3-0-0-3CS204
    3CS305Lab: Software Engineering0-0-3-0CS301
    4CS401Data Science and Analytics3-0-0-3CS201
    4CS402Cloud Computing3-0-0-3CS204
    4CS403Human-Computer Interaction3-0-0-3CS202
    4CS404Mobile Application Development3-0-0-3CS202
    4CS405Lab: Mobile Application Development0-0-3-0CS404
    5CS501Machine Learning3-0-0-3CS303
    5CS502Embedded Systems3-0-0-3CS203
    5CS503Internet of Things3-0-0-3CS204
    5CS504Web Technologies3-0-0-3CS404
    5CS505Lab: Web Technologies0-0-3-0CS504
    6CS601Advanced Artificial Intelligence3-0-0-3CS501
    6CS602Distributed Systems3-0-0-3CS204
    6CS603Big Data Analytics3-0-0-3CS401
    6CS604Security Protocols3-0-0-3CS304
    6CS605Lab: Distributed Systems0-0-3-0CS602
    7CS701Research Methodology3-0-0-3CS301
    7CS702Capstone Project3-0-0-3CS501, CS601
    7CS703Project Management3-0-0-3CS301
    7CS704Entrepreneurship3-0-0-3None
    7CS705Lab: Capstone Project0-0-3-0CS702
    8CS801Internship0-0-0-6CS702
    8CS802Final Year Thesis0-0-0-6CS702

    Advanced Departmental Electives

    Departmental electives in the Computer Science program are designed to provide students with in-depth knowledge in specialized areas. These courses are offered in the later semesters and are often research-oriented. Here are some of the advanced departmental electives offered:

    • Advanced Machine Learning: This course covers advanced topics in machine learning such as reinforcement learning, deep learning architectures, and neural network optimization. Students will learn to apply these techniques to real-world problems in various domains.
    • Blockchain Technologies: This course explores the fundamentals of blockchain, smart contracts, and decentralized applications. Students will understand the underlying principles of distributed ledger technology and its applications in finance, supply chain, and more.
    • Quantum Computing: This course introduces students to the principles of quantum computing, including quantum algorithms, quantum error correction, and quantum cryptography. It provides a foundation for understanding the future of computing.
    • Computer Vision: This course focuses on the techniques and algorithms used in computer vision, including image processing, object detection, and recognition. Students will gain hands-on experience with tools like OpenCV and TensorFlow.
    • Natural Language Processing: This course covers the techniques and models used in processing and understanding human language. Students will learn about text classification, sentiment analysis, and language generation.
    • Mobile and Wireless Networks: This course explores the architecture and protocols of mobile and wireless networks. Students will study topics such as 5G, IoT, and mobile security.
    • Computer Graphics and Visualization: This course introduces students to the principles and techniques of computer graphics, including rendering, animation, and visualization. Students will work with tools like OpenGL and Unity.
    • Network Security: This course covers advanced topics in network security, including intrusion detection, firewall design, and secure network protocols. Students will learn to protect networks from cyber threats.
    • Software Testing and Quality Assurance: This course focuses on the principles and practices of software testing, including test planning, automation, and quality assurance methodologies. Students will gain experience with testing tools and frameworks.
    • Advanced Database Systems: This course covers advanced topics in database systems, including distributed databases, NoSQL systems, and data warehousing. Students will learn to design and implement scalable database solutions.

    Project-Based Learning Philosophy

    The Computer Science program at University of Petroleum and Energy Studies Dehradun places a strong emphasis on project-based learning. This approach ensures that students apply theoretical knowledge to practical problems, fostering innovation and critical thinking. The program includes mandatory mini-projects in the second and third years, followed by a comprehensive final-year thesis or capstone project.

    The mini-projects are designed to be interdisciplinary, allowing students to collaborate with peers from other departments and gain exposure to real-world challenges. These projects are typically completed in teams and are supervised by faculty members with expertise in the relevant domains. Students are encouraged to select projects that align with their interests and career goals, with faculty mentors providing guidance and support throughout the process.

    The final-year thesis or capstone project is a significant component of the program, requiring students to conduct independent research or develop a comprehensive solution to a complex problem. Students work closely with faculty mentors to define their project scope, develop methodologies, and present their findings. The project is evaluated based on the quality of the research, the innovation of the solution, and the clarity of the presentation. This experience prepares students for graduate studies or professional roles in industry.

    Students are provided with resources and support to ensure the success of their projects. The university's research centers and laboratories offer access to cutting-edge tools and technologies, enabling students to conduct high-quality research. The program also includes workshops and seminars to help students develop project management and presentation skills.