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COURSE OVERVIEW

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An M.Tech (Master of Technology) in Computer Science and Engineering (CSE) is a postgraduate program designed to provide advanced knowledge and practical skills in computer science. The program bridges theoretical foundations with modern technological advancements, preparing students to tackle complex computing challenges. It is ideal for those aiming for careers in cutting-edge tech industries, research, or academic roles. Students gain exposure to current trends in computing such as artificial intelligence, cloud computing, and cybersecurity. The curriculum is a blend of coursework, hands-on labs, and research-oriented projects, encouraging innovation and problem-solving. Through electives and specializations, students can tailor their studies to align with personal interests and industry demands. By the end of the program, graduates are equipped with the skills to design, develop, and optimize intelligent and scalable computing systems. The program also fosters collaboration through seminars, projects, and case studies. Graduates often emerge as thought leaders, ready to contribute meaningfully to the evolving landscape of technology. With a strong foundation in both academic and applied aspects, M.Tech CSE graduates are well-positioned to shape the future of digital innovation.


Syllabus >
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PROGRAMME OBJECTIVES

  • To provide students with advanced knowledge in specialized areas such as Artificial Intelligence, Machine Learning, and Cybersecurity.
  • To encourage original research and innovation, enabling students to contribute to the field of Computer Science.
  • To establish strong ties with the industry for practical exposure and real-world applications.
  • To promote interdisciplinary approaches, integrating concepts from Data Science, Software Engineering, and Network Design.

PROGRAMME HIGHLIGHTS

Courses are designed to cover cutting-edge technologies such as AI/ML, Data Science, Cloud Computing, and Cybersecurity, ensuring graduates are industry-ready.
Emphasis on lab work, real-world case studies, and a final-year thesis or capstone project to develop strong research and problem-solving skills.
Students can choose from various electives or focus areas like Data Science, AI, Cybersecurity, or networks on their interests and career goals.
The program provides a solid foundation in research methodologies, making it an ideal stepping stone for doctoral studies or academic positions.
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Programme Curriculum

  • 3 Week Induction Program

    Course Code

    Course Name

    		 Periods

    per week

    		 Credits Hours per week
    L T P
    MTCT6501 Mathematical Foundations of Computer Science 2 1 0 3 3
    SOTT6301 Advanced Data Structures and Algorithms 2 1 0 3 3
    Program Elective – I
    MTCT6601a Deep Learning 3 0 0 3 3
    MTCT6601b Natural Language Processing
    MTCT6601c Generative AI
    Program Elective – II
    MTCT6602a Enterprise Cloud Concepts 3 0 0 3 3
    MTCT6602b Data Science
    MTCT6602c No SQL Databases
    SOTT6302 Research Methodology and IPC 2 0 0 2 2
    SOTT6303 Human Values & Professional Ethics (Audit Course – I) 2 0 0 0 2
    MTCS6501/MTCC6501 Technical Seminar/Case study 1 0 0 1 1
    SOTL6301 Advanced Data Structures and Algorithms Lab 0 0 4 2 4
    MTCJ6501 Cloud Architecture 1 0 2 2 3
    — Mentoring 0 0 0 0 1
    — Library 0 0 0 0 2
    — Physical Activity 0 0 0 0 2
    — Extra-Curricular Activities 0 0 0 0 2
    — Co-Curricular Activity 0 0 0 0 2
    — Self-Learning 0 0 0 0 3
    TOTAL 16 2 6 19 36

  • Course Code

    Course Name

    		 Periods

    per week

    		 Credits Hours per week
    L T P
    SOTT6304 Advanced Machine Learning 2 1 0 3 3
    MTCT6502 Advanced Computer Networks 2 1 0 3 3
    Program Elective – III
    MTCT6603a Ethical Hacking and Penetration Testing 3 0 0 3 3
    MTCT6603b Digital Forensics
    MTCT6603c Database Security and Privacy
    Program Elective – IV
    MTCT6604a Advanced Wireless Sensor Networks 3 0 0 3 3
    MTCT6604b Advanced Wireless Adhoc Networks
    MTCT6604c Quantum Computing
    SOTT6305 English for Research Paper Writing

    (Audit Course II)

    		 2 0 0 0 2
    MTCP6501 Mini Project with Technical Seminar 0 0 8 4 8
    SOTL6302 Advanced Machine Learning Lab 0 0 4 2 4
    MTCL6501 Advanced Computer Networks Lab 0 0 4 2 4
    — Mentoring 0 0 0 0 1
    — Co-Curricular Activities 0 0 0 0 1
    — Self-Learning 0 0 0 0 1
    — Extra-Curricular Activities 0 0 0 0 2
    — Library 0 0 0 0 1
    TOTAL 12 2 16 20 36

  •  Course Code

    Course Name

    		 Periods

    per week

    		 Credits Hours per week
    L T P
    MTCM7501 MOOC – 1 3 0 0 3 3
    MTCM7502 MOOC – 2 3 0 0 3 3
    MTCP7501 Dissertation I / Industrial Project 0 0 20 10 20
    — Mentoring 0 0 0 0 1
    — Co-curricular activity 0 0 0 0 2
    — Self-Learning 0 0 0 0 1
    — Physical Activity 0 0 0 0 2
    — Extra-curricular activities 0 0 0 0 2
    — Soft Skills Training 0 0 0 0 1
    — Certification Course 0 0 0 0 1
    TOTAL 6 0 20 16 36

  • Course Code

    Course Name

    		 Periods

    per week

    		 Credits Hours per week
    L T P
    MTCP7502 Dissertation Phase II 0 0 32 16 32
    TOTAL 0 0 32 16 32

PROGRAMME FEE AND SCHOLARSHIPS

PROGRAMME FEES SCHOLARSHIPS ADMISSION PROCESS
One Time Fee Admission Fee ₹10,000
Year I Tuition Fee + Annual Recurring Fee ₹ 1,50,000 + ₹ 13,000
Year II Tuition Fee + Annual Recurring Fee ₹ 1,50,000 + ₹ 13,000
Total Programme Fee (2 Years) ₹ 3,36,000

Scholarship is available for eligible students

Admissions are conducted in two modes:
1. Convener Quota: As per the Andhra Pradesh Private Universities Act, through the Government of Andhra Pradesh.
2. University Quota: Based on the TAU entrance exam or recognized national-level exams.

Eligibility

Pass with 50% aggregate marks (45% for reserved categories) in B.Tech. (Computer Science and Engineering or Information Technology or Electronics and Communication Engineering or Electrical and Electronics Engineering) or MCA or M.Sc. (Information Technology or Computer Science) or equivalent.

EMPLOYABILITY AREAS

Graduates are equipped to work in research labs, biotech industries, diagnostics, and healthcare sectors. Prominent roles include:

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  • Software Engineer
  • Senior Software Engineer
  • Software Developer
  • AI/Machine Learning Engineer
  • Cybersecurity Analyst
  • Assistant Professor
  • Project Fellow or Ph.D. Scholar