Why AI&DS from FXEC

Industry Supported Laboratories

Data Science Industrial Applied Lab

Academic Partnerships

Esterling, Chicago

Maxelerator Foundation

3i Infotech

Research

No.of Paper Publication Last 2 Years - 8

admission-process

Programme Overview

The department of Artificial Intelligence and data science was established on October 2021. This Department has 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. The faculty members are expertized with machine learning, data science and big data analytics.

  • 714+ Total Offers
  • 315 Internship with Salary
  • 17 Lac Per Annum Highest Package
  • 126 Companies Recruited
Vision

To impart quality education and produce high quality, creative and ethical engineers, instill professionalism, enhance students problem-solving skills in the domain of artificial intelligence and data science with a focus to prepare them for the industry, engage them in potential research areas, to pursue and have continued professional growth to serve the greater cause of society.

Mission
  1. To provide skill-based education to master the students in problem solving and analytical skills to enhance their niche expertise in the field Artificial Intelligence and Data Science.
  2. To educate the students with latest technologies to update their knowledge in the field of AI and Data science. To enable students to experience content-based learning with premier quality data science education, research, industrial collaboration and to become an successful entrepreneur recognized globally.
  3. To guide students in research on Artificial Intelligence and data science, with aim of having an ethical impact on society by tackling societal grand challenges.

PEO, PO, PSO

B.Tech – Artificial Intelligence & Data Science
  1. PEO1: To Formulate, analyse and solve Engineering problems with strong foundation in Mathematical, Scientific, Engineering fundamentals and modern computing practices through advanced curriculum.
  2. PEO2: Analyze the requirements, realize the technical specification and design the Engineering solutions by applying Artificial Intelligence and Data Science theory and principles.
  3. PEO3: Demonstrate technical skills, competency in AI and DS and promote collaborative learning and team work spirit through multi - disciplinary projects and diverse professional activities.
  4. PEO4: Equip the graduates with strong knowledge, competence and soft skills that allow them to contribute ethically to the needs of society and accomplish sustainable progress in the emerging computing technologies through life-long learning.
  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 analyse 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 modelling 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 them to one‟s own work, as a member ad 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. PSO1: Implement Artificial Intelligence and data science techniques such as search algorithms, neural networks, machine learning and data analytics for solving a problem and designing novel algorithms for successful career and entrepreneurship.
  2. PSO2: Apply the skills in the areas of health care, education, agriculture, intelligent transport, environment, smart systems and in the multi-disciplinary area of Artificial Intelligence and Data Science.
  3. PSO3: Graduates will acquire practical competency with emerging technologies and open source platforms related to areas of Artificial Intelligence and Data Science.

Industry Institute Partnership

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