B.Tech Artificial Intelligence and Data Science

AI and Data Science is an innovative area of study which has emerged as a key area for the future which has reshaped our work and life style. Artificial Intelligence (AI) is any technique that enables computers to mimic human intelligence. AI is an interdisciplinary science with multiple approaches to build smart machines capable of performing tasks that typically require human intelligence. Data Science (DS) is an umbrella term for a group of fields that are used to analyze large datasets. It is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data.

GIT, one of the best Engineering college in Kottayam, offers 4-year undergraduate program in Artificial Intelligence and Data Science.  The department will be driven by its commitment to excel in research, design and development of next generation cutting-edge technologies in the area of Artificial Intelligence and Data Analytics. Our mission is to cultivate industry-academia partnership, drive collaborative research with other domains and equip our talents to contribute on multi-disciplinary projects by translating the developed technology into real world impacts.

The unique undergraduate program, B.Tech. Artificial Intelligence and Data Science (AI & DS), aims the students to acquire technical skills to perform data processing, analysis and visualization in multiple real-time applications. Program envisions to equip students with the ability to identify and assess societal, health, safety and cultural issues with an emphasize on identifying their consequent responsibilities as engineers of offering optimal and effective solutions for the same.

Companies are focusing on AI-centric growth that can operate on algorithms and hence enable better customer experience. To enable the graduating students to be ready for the paradigm shift B.Tech programme in AI & DS is designed to provide the foundations for job roles like, AI Engineer, AI Data Analyst, Data Engineer, Data Scientist, etc in the evolving job market scenario.

Computer Science Engineering (CSE) also plays a critical role in these domains by offering a solid foundation in programming, software development, and computational theory. Graduates with a background in CSE are well-equipped to contribute to AI and Data Science projects with their deep understanding of algorithms, systems, and data structures.

Program Outcomes

Engineering Graduates will be able to:

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.

Program Educational Objectives (PEOS)

PEO 1 : To provide graduates with the proficiency to utilize the fundamental knowledge of basic sciences, mathematics, artificial intelligence, data science and statistics to build systems that require management and analysis of large volume of data.
PEO 2 : To enrich graduates with necessary technical skills to pursue pioneering research in the field of AI and Data Science and create disruptive and sustainable solutions for the welfare of ecosystems.
PEO 3 : To enable graduates to think logically, pursue lifelong learning and collaborate with an ethical attitude in a multidisciplinary team.

Program Specific Outcomes (PSOS)

PSO1 : Demonstrate comprehensive knowledge and practical skills of circuit design and analysis, IC design techniques and implement new designs and formulate Problems in the thrust areas of analog, RF, digital and mixed signal VLSI design.
PSO2 : Demonstrate conceptual understanding of signal processing and communications and their applications in real world systems and solve the problems in the emerging areas of wireless communications, signal Processing, coding theory, wireless networks and internet of things.
PSO3 : Apply the knowledge of the main components of IoT architecture / Artificial Intelligence for real-world applications.

Value Added Courses

1. Python Programming
2. Associate Big data Engineer
3. Associate Big Data Analyst
4. Data Science with Python
5. Blockchain Technology
6. Cyber Security
7. Cloud Computing
8. Virtual Reality