TCS - 305 (7 Lacs Salary, 3.86 Lacs Salary & 3.36 Lacs Salary), DXC - 193 (4.20 Lacs Salary), VIRTUSA - 172 (7.5 Lacs Salary & 5.5 Lacs Salary), MINDTREE - 119 (6.5 Lacs Salary, 5 Lacs Salary & 4 Lacs Salary), COGNIZANT - 95 (6.75 Lacs Salary & 4 Lacs Salary), HEXAWARE - 90 (6 Lacs Salary & 4 Lacs Salary ), CAPGEMINI - 83 (7.5 Lacs Salary, 5.75 Lacs Salary & 4.25 Lacs Salary), ACCENTURE - 49(4.5 Lacs Salary), TECH MAHINDRA – 46 (5.5 Lacs Salary & 3.25 Lacs Salary), NTT DATA – 30 (3.5 Lacs Salary), ZOHO – 24 (8.4 Lacs Salary, 7 Lacs Salary & 5.6 Lacs Salary)

Artificial Intelligence & Machine Learning

About the Department

CSE (Artificial Intelligence & Machine Learning) is one of the top performing departments of the Institute and the most sought over branch by the students. This program is designed to provide students with the fundamentals of computer science along with emerging courses like Artificial Intelligence, Machine Learning and Deep learning. AI&ML programs are often offered in collaboration with industry partners, which gives students the opportunity to gain real-world experience and learn about the latest trends and technologies .AI &ML students will learn about basic engineering techniques, which include Engineering Mathematics, Physics, Chemistry, Engineering Graphics and Programming for Problem Solving (C language)during First Year. In the second year, they are exposed to core computer science courses like data structures, Databases, Algorithms, Operating systems, Java, Python. In the third and final year, they will start learning emerging courses like Artificial Intelligence, Machine Learning, Soft computing, Natural Language processing, Deep Learning, Computer Vision, Cloud computing, Data Science, Social Network Analysis, NoSQL Data bases along with computer science courses. The Department adopted Outcome-Based Education (OBE) and has an adequate infrastructure with state-of-the-art laboratories and other supporting facilities to provide enhanced learning environment. AI&ML graduates will be in high demand for their skills in developing, deploying, and managing AI&ML systems.

To provide students with a comprehensive knowledge on Artificial Intelligence and Machine Learning principles, techniques and applications to meet the real world entities.

  • To encourage highly innovative and ethical computer professionals by providing superior instruction, training, and research.
  • To create professionals that are capable of working across borders, driven to master new technology, and creative in how they tackle problems in the real world.
  • To encourage faculty members and students to engage in research that will benefit society.

PROGRAMME EDUCATIONAL OBJECTIVES

PEO1: Apply their technical competence in computer science to solve real world problems, with technical and people leadership.

PEO2: Conduct cutting edge research and develop solutions on problems of social relevance.

PEO3: Work in a business environment, exhibiting team skills, work ethics, adaptability and lifelong learning.

PEO4: To develop professionally ethical individuals enhanced with analytical skills, communication skills and organizing ability to meet industry requirements.

PROGRAM OUTCOMES (PO)

1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems

2. 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

3. 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

4. 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

5. 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

6. The engineer and society: 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

7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development

8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice

9. Individual and team work: Function actively and efficiently as an individual or a member/leader of different teams and multidisciplinary projects.

10. Communication: Communicate efficiently the engineering facts with a wide range of engineering community and others, to understand and prepare reports and design documents; to make effective presentations and to frame and follow instructions.

11. 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

12. 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

Program Specific outcomes

PSO1

Exhibit design and programming skills to build and automate business solutions using cutting edge technologies.

PSO2

Strong theoretical foundation leading to excellence and excitement towards research, to provide elegant solutions to complex problems.

Intake

STUDENTS STRENGTH

Year No of Students Boys Girls
I AIML A
62
40
22
I AIML B
64
40
24
II AIML
61
42
19
TOTAL
187
122
65

SEMESTER WISE RESULT

Academic Year 2023-2024 (EVEN Semester) – APR/MAY 2024 Examinations

Class/ Semester Total No. of Students Total No. of Students Appeared Total No. of Students Passed Total No. of Students Failed Overall Pass Percentage (%)
I / II
61
61
53
8
86.81

NEWS & EVENTS

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