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B.Tech in Artificial Intelligence and Data Science

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About B.Tech in AI & DS

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B.Tech Artificial Intelligence & Data Science at  KMCT College of Engineering For Emerging Technologies and Management,Vadakara is a four-year undergraduate programme designed to equip students with a strong foundation in artificial intelligence, machine learning, data analytics, and modern computing technologies. The programme focuses on combining theoretical knowledge with practical skills to prepare students for the rapidly evolving technology landscape.

The curriculum covers essential topics such as programming, data structures, algorithms, database management, cloud computing, and computer networks, along with specialized subjects in artificial intelligence, machine learning, deep learning, natural language processing, big data analytics, and predictive modeling. Students are also trained in software development, data visualization, and applied AI solutions to solve real-world problems.

KMCT emphasizes hands-on learning through state-of-the-art laboratories, projects, internships, workshops, and industry collaborations. Students are encouraged to participate in research, innovation challenges, hackathons, and seminars to develop analytical thinking, problem-solving skills, and technical competence.

Graduates of the programme are well-prepared for careers in artificial intelligence, data science, machine learning engineering, business analytics, and research. Alongside technical expertise, the programme focuses on developing communication skills, ethical values, teamwork, and adaptability, enabling students to succeed in both national and global technology sectors.

Program Outcomes (POs)

  1. 1. Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  2. 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. 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 public health and safety, and cultural, societal, and environmental factors.
  4. 4. Conduct Investigations of Complex Problems: Use research-based knowledge, including design of experiments, analysis and interpretation of data, and synthesis of information, to provide valid conclusions.
  5. 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. 6. The Engineer and Society: Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal, and cultural issues, and the consequent responsibilities relevant to professional engineering practice.
  7. 7. Environment and Sustainability: Understand the impact of professional engineering solutions in societal and environmental contexts and demonstrate the knowledge of, and need for, sustainable development.
  8. 8. Ethics: Apply ethical principles and commit to professional ethics, responsibilities, and norms of engineering practice.
  9. 9. Individual and Teamwork: Function effectively as an individual, and as a member or leader in teams, and in multidisciplinary settings.
  10. 10. Communication: Communicate effectively with the engineering community and with society at large. Comprehend and write effective reports and documentation, make effective presentations, and give and receive clear instructions.
  11. 11. Project Management and Finance: Demonstrate knowledge and understanding of engineering and management principles and apply these to one's own work, as a member and leader in a team. Manage projects in multidisciplinary environments.
  12. 12. Life-Long Learning: Recognize the need for, and have the preparation and ability to engage in independent and lifelong learning in the broadest context of technological change.

Program Educational Objectives (PEOs)

  • Technical Expertise: Graduates will possess a deep understanding of AI and data science principles, enabling them to solve complex problems and advance in their careers or further studies.

  • Professional Skills: Graduates will demonstrate strong analytical, problem-solving, and ethical skills, preparing them to meet industry demands and contribute responsibly to the field.

  • Innovation and Leadership: Graduates will be equipped to drive innovation and lead projects in AI and data science, leveraging their knowledge to make impactful contributions across various industries.

Program Specific Outcomes (PSOs)

  • AI Model Development: Students will be proficient in designing, developing, and deploying machine learning and deep learning models to solve real-world problems across different domains.

  • Data Analytics and Visualization: Students will have the ability to analyze large datasets, apply statistical techniques, and create visualizations to extract meaningful insights and support data-driven decision-making.

  • AI Applications and Ethical Practices: Students will be skilled in applying AI technologies to various industries while adhering to ethical guidelines and addressing societal impacts, ensuring responsible and impactful use of AI solutions.

Curriculam