Artificial Intelligence & Machine Learning

Artificial Intelligence & Machine Learning

About Department

Artificial Intelligence and machine Learning (AI&ML) is a new, emerging field which consists of a set of tools and techniques used to extract useful information from data. AI&ML is a fast growing discipline and is full of rigorous practical analysis. The demand for undergraduates in AI and ML has industry required skills and demand in the Global market over the last few years. Artificial Intelligence and Machine Learning is also in line demand with computer science. Machine learning is an established research discipline. However, recent advances have increased the impact on many areas of society, science, medicine, and everyday life.AI with ML is in demand in the robotics applications, space technology, industry4.0 and many more.AI and ML delivers modern computational systems that demonstrate capabilities of perception, reasoning, learning and action that are typical of human intelligence.

B.Tech. Artificial Intelligence and Machine Learning programme emerging area is start, in our College, from the academic year 2021– 22 with a vision to emerge as a premier center for education and research in Artificial Intelligence and Machine Learning and in transforming students into innovative professionals of contemporary and future technologies to cater the global needs of human resources. AI and ML course aims to indulge knowledge in not only the core technologies such as artificial intelligence, data mining and data modelling and also make ready students expertise in thrust areas such as machine learning, and deep learning. Students with this course can gain thorough knowledge in: Intelligent Systems, Machine Learning, Deep Learning, Reinforcement Learning, Natural Language Processing, and Technologies for machine learning with cloud computing, big data analytics Reasoning, Internet of Things, Statistical Learning and visualization skills. The goal of artificial intelligence (AI) and machine learning is to program computers to use example data or experience to solve a given problem. Many successful applications based on machine learning exist already, including systems that analyse past sales data to predict customer behaviour (financial management), recognize faces or spoken speech, optimize robot behaviour so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data.

This graduate program has a comprehensive coverage of applied and statistical methods used in Machine Learning 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 in machine learning applications, and data management, with the objective of creating innovative strategies to solve challenging real-world problems.

Career opportunities in Artificial Intelligence and Machine Learning are Data Scientist, Machine Learning Engineer, Research Scientist, Business Intelligence Developer, Product Manager, and Robotics 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 Machine Learning is to impart quality education and produce high quality, creative and ethical engineers, in still professionalism, enhance students' problem solving skills in the domain of artificial intelligence and Machine Learning To emerge as a premier center for education and research in Artificial Intelligence and Machine Learning and in transforming students into innovative professionals of contemporary and future technologies to cater the global needs of human resources for IT and ITES companies.

  • 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 Machine Learning.
  • To explore opportunities for skill development in the application of Artificial Intelligence and Machine learning among rural and under privileged population.
  • Transform professionals into technically competent through innovation and socially responsible.
  • To promote research based projects and activities among the students in the emerging areas of Artificial Intelligence and Machine Learning.
  • 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 Machine Learning 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.

A graduate of Computer Science & Engineering will have ability to:

  1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  8. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings
  9. Communication: Communicate effectively on complex engineering activities with then 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.
  10. 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
  11. 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 Machine Learning in terms of underlying statistical and computational principles and apply the knowledge to solve practical problems.
PSO2 Learn the basic concepts of Artificial Intelligence and Machine Learning and to apply them to various areas, like Image Processing, Speech Recognition, Product Recommendations, Medical Diagnosis etc.
PSO3 Solutions to complex problems, using latest hardware and software tools, along with analytical skills to arrive at cost effective and appropriate solutions.

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