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B.E.

B.E. in Computer Science & Engineering (AI & ML)

AICTE

Approved Intake

120

Duration

4 Years

Accreditation

AICTE

About the Programme

This programme blends core computer science with specialised study of AI, machine learning, deep learning, NLP and computer vision, preparing students to design and deploy intelligent systems responsibly. The Department has state-of-the-art laboratories and classroom facilities. The department regularly conducts Bootcamps, Technical Seminars, Workshops, Faculty Development Programs and Hackathons. The department encourages the students to participate in cocurricular and extracurricular activities. The department has established strong collaborations with Industries and premier peer Institutes to design the curriculum to meet the global standards in the domains of Cyber Security.The department is partnering with Ramaiah Medical and Dental College to work on projects which has societal impact. The department is having collaborations with Industries like SAP Labs, Unisys, IBM, HPE, Samsung, Microsoft, GE Healthcare, Adobe, Thomson Reuters, Yubi, JP Morgan, Intellytix etc. to support Internships, Projects, Curriculum upgradation, Guest Lectures, and Industry Visits.

Vision

To produce AI/ML engineers with strong fundamentals and an ethical, innovative mindset.

Mission

Impart quality technical education through effective teaching–learning processes. Promote research, innovation and industry-institute interaction for societal benefit. Inculcate professional ethics, leadership and life-long learning among students. Produce competent professionals ready to address global and local challenges.

Programme Educational Objectives (PEOs)

  • 1

    PEO1: Excel in professional career by acquiring knowledge in basic sciences and Computer Science and Engineering, Artificial Intelligence & Machine Learning principles and contribute to the profession as an excellent employee, or as an entrepreneur.

  • 2

    PEO2: Capable of pursuing higher education and research.

  • 3

    PEO3: Adapt to technological advancements in multidisciplinary environments by engaging in lifelong learning with leadership qualities, professional ethics and soft skills.

Programme Outcomes (POs)

1

The Outcomes of the Bachelor of Engineering in Computer Science & Engineering

2

(Artificial Intelligence and Machine Learning) Programme are as follows:

3

PO1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems. (WK3)

4

PO2: Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences. (WK2)

5

PO3: Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations. (WK3)

6

PO4: Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions. (WK4)

7

PO5: Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations. (WK3)

8

PO6: The engineer and the world: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice. (WK1)

9

PO7: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice. (WK9)

10

PO8: Individual and teamwork: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.(WK9)

11

PO9: Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions. (WK9)

12

PO10: Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments. (WK5)

13

PO11: Life-long learning: Recognize the need for and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change. (WK6)

Programme Specific Outcomes (PSOs)

  • 1

    PSO1: Ability to understand and identify problems/opportunities where CSE, AI and ML concepts can be applied and to identify the right AI and ML techniques in such contexts.

  • 2

    PSO2: Ability to perform the data engineering, designing, developing and testing the AI and ML solutions that include both hardware and software.

  • 3

    PSO3: Ability to be aware of technical solutions that are following ethical aspects aligning with social responsibilities both at designing and evelopmental phases of

  • 4

    applications.n tools.

Top Recruiters & Industry Collaboration

Google Microsoft Amazon Nvidia Fractal Analytics Adobe Walmart Global Tech

Career Options

Machine Learning Engineer, Data Scientist, AI Engineer, Computer Vision Engineer, NLP Engineer, MLOps Engineer, Research Engineer and Entrepreneur

Scheme & Syllabus

First Year Fourth Year
2022 – Scheme and Syllabus 2018 – Scheme and Syllabus

B.E. Curriculum Structure (4 Years)

Curriculum Component Credits (% of total) Contact Hours
Basic Sciences 14 23
Engineering Mathematics 12 20
Humanities & Social Sciences 8 12
Engineering Sciences & Foundation 18 28
Professional Core 62 90
Professional Electives 18 26
Open Electives 9 12
Project / Internship / Seminar 19
Total 160