Computer Science And Engineering (Artificial Intelligence)

MITS Computer Science And Engineering (Artificial Intelligence)

B.Tech in CSE(Artificial Intelligence)

B.Tech in Computer Science And Engineering (Artificial Intelligence) is an under graduate programme offered by the department of AI & DS. The programme imparts knowledge on the basic principles of AI. The programme will foster students’ ability to apply the AI models and techniques to develop software solutions for complex real world intelligence applications. Artificial intelligence is all about making machines capable of human-like decision-making and acting. As the world is getting automated with various upcoming paradigms like Big data, Robotics, Internet of Things etc., bringing up artificial intelligence becomes inevitable. Autonomous devices, like robots, use machine learning approaches to combine algorithms with experiences. AI is set to disrupt practically every industry imaginable. Aim of the programme is to equip the students with the knowledge on foundational principles, algorithms and learning techniques in the field of AI. In future, students will be able to handle machine learning and automation tasks, which have wide application in the industry in terms of mechanical systems and data science.

 


 

B.Tech in CSE(Artificial Intelligence)
B.Tech in CSE(Artificial Intelligence)
B.Tech in CSE(Artificial Intelligence)
B.Tech in CSE(Artificial Intelligence)
B.Tech in CSE(Artificial Intelligence)
B.Tech in CSE(Artificial Intelligence)
B.Tech in CSE(Artificial Intelligence)
B.Tech in CSE(Artificial Intelligence)
B.Tech in CSE(Artificial Intelligence)
B.Tech in CSE(Artificial Intelligence)

Opportunities

PEOs
PSOs
POs
PEO1

Graduates will be able to design  & develop AI models to automate various real world applications.

PEO2

Graduates will be empowered to use AI responsibly in research, development and technology transfer.

PEO3

Graduates will be able to contribute to the advancement of society and uphold the values of sustainability and inclusivity

PSO1

  • Implement AI models and strategies for real world problems to meet the challenges of future.


 

PSO2

Develop computational models for system automation.

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 teamwork: 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.

What you will learn

Core Courses

Introduction to Artificial Intelligence

Machine Learning 

Agent Based Intelligent Systems

Robotics and Automation

Introduction to Deep Learning

 

Electives

Pattern Recognition

Nature Inspired Computing Techniques

Soft Computing

Artificial Neural Networks Techniques

Knowledge Engineering

Natural Language Processing

Big Data Analytics

Labs & Projects

AI Algorithms Lab

Machine Learning Lab

Robotics Lab

Mini Project

Major Project

Syllabus / Curriculum

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