Artificial Intelligence & Data Science

Information Technology

About Department

Artificial Intelligence and Data Science (AI&DS) is a new, exponentially emerging field which consists of a set of tools and techniques used to extract useful information from data. AI&DS is a fast growing discipline and is full of rigorous practical analysis. The demand for undergraduates in AI and DS has experienced an increasing demand in the Global market over the last few years. Building human-level thought processes through the creation of artificial intelligence (AI) is the state-of-the-art in Computer Science. Intelligent machines are influenced by emerging technologies, smart devices, sensors, computing power, faster data processing, huge storage and human-machine interaction capabilities. Data Science (DS) is an interdisciplinary field with the ability to extract knowledge/insights from data - be it structured, unstructured, or semi-structured data. AI with DS, is in demand with the extensive usage of smart phones, innovations in social media, online banking, etc.., and more efficient and powerful solutions to smart environments including Internet of Things and Industry 4.0. AI and DS delivers data driven solution using computational principles, methods and systems for extracting knowledge from data and modern computational systems that demonstrate capabilities of perception, reasoning, learning and action that are typical of human intelligence.

B.Tech. Artificial Intelligence and Data Science programme kick-starts, in our College, from the academic year 2020 – 21 with a vision to build the intellectual capital of the society through research-based education, creating new knowledge and innovations. AI and DS course aims to indulge knowledge in not only the core technologies such as artificial intelligence, data warehousing, data mining and data modelling and also make ready students expertise in thrust areas such as machine learning and big data analytics. Students with this course can gain thorough knowledge in: Intelligent Systems, Machine Learning, Deep Learning, Reinforcement Learning, Natural Language Processing, Text Technologies for Data Science, Data Analytics and Mining, Big Data Management, Data Visualization, Bayesian Data Analysis, Probabilistic Modeling and Reasoning, Cloud Technologies, Internet of Things, Statistical Learning and visualization skills.

This graduate program has a comprehensive coverage of applied mathematics used in data science and artificial intelligence while preparing the students to analyze, design and experiment solutions to problems. The curriculum targets technical and design skills, AI knowledge, and competencies needed to master strategic analytical methods and tools, and data management, with the objective of creating innovative strategies to solve challenging real-world problems.

Career opportunities in Artificial Intelligence and Data Science are Data Scientist, Knowledge Engineer, Data Engineer, Business Analyst, Data Analyst, Business Intelligence Engineer and Research Scientist.

The faculty members are highly motivated and devoted in delivering the highest quality professional education to students, and strive to excel in their research areas.

The vision of the Department of Artificial Intelligence and Data Science is 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.

  • 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.
  • 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 and industrial collaboration.
  • 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.
  • To impart quality and value based education and contribute towards the innovation of computing system, data science to raise satisfaction level of all stakeholders

S.No. Programme Educational Objectives
PEO1 To Formulate, analyze and solve Engineering problems with strong foundation in Mathematical, Scientific, Engineering fundamentals and modern computing practices through advanced curriculum.
PEO2 Analyze the requirements, realize the technical specification and design the Engineering solutions by applying artificial intelligence and data science theory and principles.
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.
PEO4 Equip the graduates with strong knowledge, competence and soft skills that allows them to contribute ethically to the needs of society and accomplish sustainable progress in the emerging computing technologies through life-long learning.

Engineering Graduates will be able to

S.No. PROGRAM OUTCOMES (POs)
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 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.
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.

S.No. Programme Specific Outcomes
PSO1 Understand, analyze and develop essential proficiency in the areas related to artificial intelligence and data science in terms of underlying statistical and computational principles and apply the knowledge to solve practical problems.
PSO2 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.
PSO3 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.

Course Structure

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