Department of Artificial Intelligence and Machine Learning (AI&ML)
Overview
The Department of Artificial Intelligence and Machine Learning is a unique centre of MSEC established in 2024. This Department offers a 4 year B.E. (Artificial Intelligence and Machine Learning) Programme. It has a heartfelt team of dedicated faculty members with a sound knowledge in various areas and has the state-of-art facilities for various laboratories and supports smart class learning.
Programme
VISION
To be a centre of excellence in Computer Science and Management to develop the skilled Engineers, Managers and Entrepreneurs with morals and societal responsibilities
MISSION
i. To impart technical and Managerial knowledge through innovative teaching-learning process
ii. To inculcate the research interest among the faculty and students to instill innovation
iii. To produce engineers with managerial and entrepreneur skills to suit the industries
iv. To produce skilled engineers with ethics and social responsibilities
Programme Educational Objectives (PEOs)
| PEO1. | Technical Adeptness: | To apply the knowledge of computer science and Business principles to develop computationally intelligent solutions for global business needs. |
| PEO2. | Research and Entrepreneurship: | To enable graduates to pursue research, or have a successful career in academia or industries associated with Computer Science and Engineering, or as entrepreneurs. |
| PEO3. | Interpersonal Skills: | To produce highly qualified graduates who excel in professional careers and pursue higher education with the necessary requirements. |
| PEO4. | Awareness of Social Impact: | To ensure that the graduates will work with professionalism and ethics by contributing to the advancement of the society. |
Program Specific Outcomes (PSOs)
| PSO1. | Ability to create innovative software professionals with the emerging technologies and service orientations. |
| PSO2. | Develop and automate business solutions using cutting-edge technology by exhibiting design and programming expertise. |
| PSO3. | Ability to design and implement industry demand professionals with business principles aligned with equivalent knowledge in humanities and business systems |
Programme Outcomes (PO)
| PO1. | Engineering knowledge: | Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems. |
| 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. |
| 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. |
| PO4. | Conduct investigation of complex problem: | 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. |
| 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. |
| PO6. | 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. |
| PO7. | 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. |
| PO8. | Ethics: | Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice. |
| PO9. | Individual and team work: | Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings. |
| PO10. | 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. |
| PO11. | 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. |
| PO12. | 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. |
Department Facilities
| Description | No of Rooms | Total Area (m2) |
|---|---|---|
| Class Rooms | UG - 6, PG - 2 | 472.25 |
| Faculty Rooms | HOD - 1, Faculty - 2 | 112.8 |
| Seminar Hall | 1 | 150.35 |
| Department Library | 1 | 40.80 |
| R & D Cell | 1 | 58.20 |
| Laboratories | 8 | 412.50 |
PG & R&D Laboratory
| NO OF TERMINALS | 29 | 1 |
| PROCESSOR | CORE I5 | Core 2 Quad |
| PROCESSOR SPEED | 6.4 GHz | 4.6Ghz |
| RAM | 8 GB | 2 GB |
| HARD DISK | 500 GB | 250 GB |
| MOTHER BOARD | DELL | DELL |
Linux & Unix Laboratory
XEON SERVER |
CORE 2 DUO |
||
No of Terminal : 1 |
No of Terminal : 30 |
||
| PROCESSOR | INTEL XEON | PROCESSOR | CORE 2 DUO |
| PROCESSOR SPEED | 2.67 GHz | PROCESSOR SPEED | 2.67 GHz |
| RAM | 2 GB | RAM | 1 GB |
| HARD DISK | 260 GB | HARD DISK | 160 GB |
| MOTHER BOARD | INTEL | MOTHER BOARD | INTEL |
System Software Laboratory
CORE 2 DUO |
|
No of Terminal : 30 |
|
| PROCESSOR | CORE 2 DUO |
| PROCESSOR SPEED | 2.67 GHz |
| RAM | 1 GB |
| HARD DISK | 160 GB |
| MOTHER BOARD | INTEL |
DBMS Laboratory
| PROCESSOR | Core 2 Duo Processor |
| PROCESSOR SPEED | 3 GHz |
| RAM | 2 GB |
| HARD DISK | 160 GB |
| MOTHER BOARD | INTEL |
Case Tools Laboratory
CORE 2 Duo |
CORE 2 QUAD |
||
No of Terminal : 11 |
No of Terminal : 24 |
||
| PROCESSOR | CORE 2 Duo | PROCESSOR | CORE 2 QUAD |
| PROCESSOR SPEED | 2.4 GHz | PROCESSOR SPEED | 2.2 GHz |
| RAM | 2 GB | RAM | 2 GB |
| HARD DISK | 160 GB | HARD DISK | 250 GB |
| MOTHER BOARD | INTEL | MOTHER BOARD | DELL |
Faculty
| Name | Qualification | Designation | Date of Joining | Nature of Association (Regular / Contract / Adjunct) |
Mrs. R. LAVANYA |
M.E., | Assistant Professor | 09/09/2024 | Regular |
Mr. K. GOPU |
M.E., | Assistant Professor | 09/09/2024 | Regular |
Academics
Semester III
| Subject Code | Subject Name | Lesson Plan | Question Bank | Lecture Notes | ICT Tools |
| Discrete Mathematics | |||||
| Digital Principles and Computer Organization | |||||
| Fundamentals of Economics | |||||
| Object Oriented Programming | |||||
| Design and Analysis of Algorithms | |||||
| Fundamentals of Data Science and Analytics |
Semester IV
| Subject Code | Subject Name | Lesson Plan | Question Bank | Lecture Notes | ICT Tools |
| Probability and Statistics | |||||
| Machine Learning | |||||
| Operating Systems | |||||
| Database Management Systems | |||||
| Introduction to Business Systems | |||||
| Environmental Sciences and Sustainability |
Semester V
| Subject Code | Subject Name | Lesson Plan | Question Bank | Lecture Notes | ICT Tools |
| Cloud Computing | |||||
| Embedded Systems and IoT | |||||
| Data and Information Security | |||||
| Big data Analytics | |||||
| Fundamentals of Management |
infrastructures
