The Department of Computer Science and Engineering at Techno Main Salt Lake offers a specialized program in Artificial Intelligence and Machine Learning. With cutting-edge research and practical applications, students gain expertise in areas such as natural language processing, computer vision, and predictive analytics. The department's highly qualified faculty and industry collaborations ensure that students are prepared for the challenges of an AI-driven world.
| Program | Intake | Duration | Entry Level |
|---|---|---|---|
| B.Tech - CSE / AI & ML | 120 | 4 Years | After Class 12 |
| B.Tech (L) - CSE / AI & ML | 12 | 3 Years | After Diploma/B.Sc |
1. To foster academic growth by imparting quality education in the field of Artificial Intelligence and Machine Learning through innovative and contemporary pedagogical methods thereby developing one’s acumen towards problem solving.
2. To identify and nourish talented and focused individuals to become leaders and/or innovators in the world of Artificial Intelligence, with the aim to create substantial number of job providers in the long run.
3. To inculcate higher moral and ethical values among the graduate engineersto become lifelong learners with a holistic approach to contribute to the sustainability and overall well-being of the society.
4. To develop inter-personal skills among individuals through intra, inter-departmental and inter-institutional activities, thereby instilling team-building qualities and boosting their employability skills to facilitate self-sustainability
5. To emerge as a prominent Centre of Excellence in the emerging areas of research related to Artificial Intelligence and its allied fields.
To be a leader in the field of Artificial Intelligence and Machine Learning education by providing a wholistic learning environment to produce quality professionals with an inclination towards research, contributing heavily to the AI industry and social engineering.
1. To excel in their profession by utilizing cutting-edge concepts and tools in the fields of Artificial Intelligence and Machine Learning for the sustainable growth of business and society.
2. To successfully apply innovative, analytical and design skills to demonstrate research capabilities in the field of Artificial Intelligence and Machine Learning.
3. To pursue lifelong learning and professional upgradation in order to adapt to the speedy advancement of tools and techniques in the field of AI and stay relevant and employable throughout.
4. To demonstrate leadership and entrepreneurial skills across multidisciplinary verticals of AI and eventually emerge as job providers for overall societal development.
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 effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
10. 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.
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.
1. Ability to apply the knowledge of human reasoning, Statistical Modeling, Artificial Intelligence, Machine Learning and data analytics to design, develop, deploy and prototype intelligent/expert systems.
2. Ability to develop analytical and computationalskills using state-of-the-art tools and techniques to solve complex real-world problems in areas related to Deep Learning, Machine learning, Artificial Intelligence etc.
3. Ability to identify and analyze research gaps in Artificial Intelligence and associated multidisciplinary areas to come up with innovative and optimal solutions for technological and socio-economic problems
| Laboratories | ||
|---|---|---|
| Applied and Adaptive Optics lab | Material Characterization lab | Data Structure Using C lab |
| Atomic and Molecular Physics lab | Statistical Mechanics & Electromagnet. Theory lab | Statistics using MAT Lab |
| Computational Physics lab | Biochemistry and Analytical Techniques lab | Micro Programming & Architecture lab |
| General Physics lab | Microbiology lab | Programming lab |
| Modern Physics lab | Genetic Engineering lab | Business presentation and language lab |
| Optics lab | Immunology lab | Object-Oriented Programming lab |
| Solid State Physics lab | Bioinformatics lab | Unix lab |
| Solid state Technology lab | Bioreactor operations lab | Graphics & Multimedia lab |
| General Chemistry lab | Food and Environmental Biotechnology lab | Basic Computer Application lab |
| Organic Chemistry lab | Molecular Biology lab | Electronic Media: Planning & Production lab |
| Inorganic Chemistry lab | Basic Microscopy & Instrumentation lab | Electronic Media: Writing, Editing & Execution lab |
| Polymer Processing lab | Cytogenetic Techniques lab | Press Photography lab |
| Polymer Technology lab | Tissue Culture Techniques lab | Film & Television: Theory & Practice lab |
| Chemical Engineering lab | Numerical Methods lab | Design & Page Make up lab |
