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B. Tech. in Computer Science & Engineering

Overview

The B. Tech in Computer Science and Engineering (CSE) is a 4-year (8-semester) undergraduate program designed to meet the dynamic demands of industry. Spanning core and advanced topics, it equips students with skills in programming, algorithms, and system design, aligning with industry needs for innovative, problem-solving professionals. Curriculum emphasizes practical skills through Design Projects, Capstone Projects, Industry Internships and hackathons ensuring graduates are job ready. Emerging technologies like machine learning, IoT and Embedded Systems, and cyber security are integrated via electives, catering to roles in industries, startups, and research. Graduates pursue careers as software engineers, data scientists, or system architects, with attractive packages meeting the industry’s need for versatile, skilled engineers.

Duration

B. Tech. (Regular): Four Years (Full-time)

B. Tech. (Lateral): Three Years (Full-time)

Programs Offered

  1. Block Chain Technologies
  2. Cloud Computing
  3. Cyber Security
  4. DevOps
  5. Full Stack Development
  6. Internet of Things (IoT)
      Commence of the course

      January 2020 & July 2020


      Course Duration

      4 Years


      Mode of Study

      Full Time Course

      Eligibility


      For Regular

      10+2 from recognized Board / Council with Minimum 50% marks in Physics & Mathematics as compulsory subjects along with one of the Chemistry / Biotechnology / Biology / Technical Vocational Subject.

      Score in JEE (Main); JEE (Advanced); Karnataka CET; COMED-K; AUEET (Alliance Undergraduate Engineering Entrance Test); or any other State-Level engineering entrance examination.


      For Lateral Entry

      Passed Diploma examination with at least 50% marks in relevant branch of Engineering and Technology.

      Passed B. Sc. Degree from a recognized University as defined by UGC, with at least 50% marks & passed 10+2 examination with Mathematics as a subject.

      A relaxation of 5% marks or its equivalent grade may be allowed for those belonging to SC / ST.


      Programme Features

      Interdisciplinary Learning: Integrates knowledge from multiple fields, enhancing problem-solving and innovation through open electives and minors, fostering versatility and adaptability to meet complex, industry-relevant challenges.

      Project Based Learning: An educational approach where students learn through hands-on, real-world projects to foster industry-relevant skills like innovation, teamwork, and problem-solving, preparing students for professional challenges.

      Industry Alignment: Curricula meet current and future industry needs integrating real-world skills, technologies, and practices into courses, often through partnerships, internships, and projects fostering relevant expertise, problem-solving, and adaptability, aligning academic learning with professional demand.

      Research Opportunities: Empower students to investigate advanced fields like AI, quantum computing, or cybersecurity through design projects, capstone projects theses, faculty partnerships, equipping them for R&D careers or advanced studies in cutting-edge technology domains.

      Course Structure - Programs Offered

      Semester Subject Title
      IV Introduction to Virtualization and Cloud Computing
      Cloud Computing Architecture and Deployment Models
      V Internet and Cloud Computing
      Network Storage Technologies
      VI Cloud Architecture and Computing
      VII Aglie Cloud Automation
      Semester Subject Title
      IV Fundamentals of cyber security
      Cyber security algorithms
      V Cyber Security Risk Management and Mitigation
      Fundamentals of Blockchain and Cryprocurrencies
      VI Mobile and Network based Ethical Hacking
      VII Cyber Security Standards Policies and Practices
      Semester Subject Title
      IV Machine Learning with Python
      Topics in Artificial intelligence
      V Algorithm for Intelligent Systems and Robotics
      Advanced Machine Learning
      VI Cognitive Analytics
      VII High Performance Computing
      Semester Subject Title
      IV Introduction to IOT
      IoT Sensor Technologies
      V IoT Architecture and its Protocols
      IoT cloud and data analytics
      VI Industrial IoT 4.0
      VII Internet of Medical Things
      Semester Subject Title
      IV Introduction to Data Analytics
      Introduction to Data Modeling and Processing
      V Bigdata Analytics
      Data Science with Python
      VI Data Warehousing and Business Intelligence
      VII Data Visualization Techniques

      Programme Structure

      Electives

      • Minor Elective I (Intellectual Property Rights)
      • Minor Elective II (Entrepreneurship Management)
      • Principles of Data communication
      • Net Technology
      • Object Oriented Modeling and Design
      • Computer organization and architecture
      • Introduction to Micro processors
      • Distributed System
      • Java Programming
      • Theory of Computation
      • Virtual Reality
      • Artificial Intelligence
      • Data Ware housing and Data Mining
      • Computer Systems Performance Analysis
      • Multi Agent System
      • Scripting Language ( Pearl & Python)
      • Mobile Computing
      • Image Processing
      • Wireless Sensor Network
      • Advanced Computer Architecture
      • Open Elective I (Data structures with C)
      • Open Elective II (Object Oriented Programming with C++)
      • Open Elective III (Computational Complexity)
      • Open Elective IV (Compiler Design)
      • Open Elective V (Data Science & Analytics)
      • Career Development Program I (Communication and Soft Skills)
      • Career Development Program II (Aptitude and Quantitative Skills)
      • Career Development Program III (Critical Reasoning and Logical Skills)
      • Career Development Program IV (Problem Solving Skills)
      • Career Development Program V (Technical Capstone)

      Note: An elective subject is offered in the B. Tech. in Computer Science and Engineering course only if a minimum number of students enroll in it.

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