B.Tech. (Artificial Intelligence)

Graduate Programmes

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Program Code 101198

Course Overview

  • Campus
  • Noida
  • Institute
  • Amity School of Engineering and Technology
  • University
  • Amity University Uttar Pradesh
  • Program Code
  • 101198
  • Eligibility

  • 60% in class X & XII and 70% in PCM for Non-sponsored category.

    Eligibility will be relaxed by 5% for Sponsored category.

    Aggregate percentage will be calculated on the basis of marks scored in English and three academic subjects (excluding second language, Physical Education, Fine Arts, Performing Arts or any other Vocational /Non Written subjects). Student should have passed all the subjects of class XII from a recognized board.

     

  • Duration
  • 4 years
  • 1st Year Non Sponsored Semester Fee (Rs. in Lacs)
  • 1.735
  • 1st Year Sponsored Semester Fee (Rs. in Lacs)
  • 2.605
 
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  • Fee Structure
  • Program Educational Objectives
  • Program Learning Outcomes
1st Year Non Sponsored Semester Fee (Rs. in Lacs) : 1.735
1st Year Sponsored Semester Fee (Rs. in Lacs) : 2.605
  • The students shall have the ability to apply knowledge of science, engineering & technology to design and develop innovative products/ solutions as per industry and societal requirements.
  • The students shall have the ability to examine the impact of engineering solutions in societal, health, safety, legal, cultural and environmental contexts.
  • The students will be able to practice professional ethics and academic integrity and demonstrate these as an individual/ team member/ leader in diverse teams and as an entrepreneur.
  • Students will be able to demonstrate professional attitudes, effective communication and behavioral skills and sustain effective performance in the professional/entrepreneurial careers.
  • The student will have the ability to support and practice independent and life-long learning for professional development.
  • The student will apply knowledge of mathematics, sciences and engineering to solve problems using concepts of computer science & engineering and Artificial Intelligence.
  • The student will identify, formulate research literature and analyze computer science & engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences
  • The student will create solutions for analyze computer science & engineering and Artificial Intelligence problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, economical, cultural, societal, and environmental considerations
  • The student will carry out investigations of problems using research-based knowledge and research methods including design of experiments, analysis and interpretation of data and synthesis of information to provide valid conclusions.
  • The student will create, select and apply appropriate techniques, resources and modern engineering and IT tools, necessary for computing practices as per the Industrial trends with an understanding of the limitations.
  • The student will apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues and consequent responsibilities relevant to the professional engineering practice.
  • The student will recognize the impact of the professional engineering solutions in political, economic, global, societal and environmental contexts and demonstrate the knowledge if and need for the sustainable development.
  • The student will apply ethical principles and practice professional ethics and responsibilities and norms of the engineering practice
  • The student will demonstrate effectiveness as an individual and as a member or leader of team assembled to undertake a common goal in multidisciplinary settings
  • The student will use effective communication to cater to both technical and non-technical audiences.
  • The student will 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 as well as to manage projects in multidisciplinary environments.
  • The student will recognize the need for, and will engage in independent and life-long learning in the broadest context of technological change and contemporary issues.

Course Structure

  • 1st Year
  • 2nd Year
  • 3rd Year
  • 4th Year

Semester 1

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Applied Mathematics- I (UG) Basic Sciences Courses 3 0 0 0 3.00 View
Engineering Physics (UG) Basic Sciences Courses 0 0 0 0 0.00 View
Engineering Mechanics (UG) Engineering Sciences Courses 3 0 2 0 4.00 View
Introduction to Computers and Programming in C (UG) Engineering Sciences Courses 2 0 2 0 3.00 View
Workshop Practices (UG) Engineering Sciences Courses 0 0 0 0 0.00 View

Semester 2

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Basic Electrical Engineering (UG) Engineering Sciences Courses 2 1 2 0 4.00 View
Engineering Graphics Lab (UG) Engineering Sciences Courses 0 0 2 0 1.00 View
Applied Mathematics - II (UG) Basic Sciences Courses 3 0 0 0 3.00 View
Introduction to Environmental Studies (UG) Engineering Sciences Courses 0 0 0 0 0.00 View
Engineering Chemistry (UG) Basic Sciences Courses 0 0 0 0 0.00 View

Semester 3

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Applied Mathematics- III (UG) Basic Sciences Courses 3 1 0 0 4.00 View
Intelligent Systems and design thinking (UG) Engineering Sciences Courses 2 0 0 0 2.00 View
Basic Electronics Engineering (UG) Engineering Sciences Courses 3 0 2 0 4.00 View
Programming in Python (UG) Engineering Sciences Courses 3 0 2 0 4.00 View
Operating System (UG) Core Courses 2 1 2 0 4.00 View
Data Structures Using C (UG) Core Courses 3 0 2 0 4.00 View
Term Paper (UG) Non Teaching Credit Courses 0 0 0 0 1.00 View

Semester 4

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Applied Mathematics-IV (UG) Basic Sciences Courses 0 0 0 0 0.00 View
Basic Simulation Lab (UG) Engineering Sciences Courses 0 0 2 0 1.00 View
Database Management Systems (UG) Core Courses 3 1 2 0 5.00 View
Digital Electronics and Computer Organization (UG) Core Courses 3 0 2 0 5.00 View
Artificial Intelligence (UG) Core Courses 3 1 2 0 5.00 View

Semester 5

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Fundamental of Machine Learning (UG) Core Courses 2 0 2 0 4.00 View
Applied Probability and Statistics (UG) Core Courses 3 0 0 0 3.00 View
Data Communication and Computer Networks (UG) Core Courses 2 1 2 0 4.00 View
Visual Computing and Animation (UG) Core Courses 2 0 2 0 3.00 View
Aptitude and Reasoning Ability (UG) Employability & Skill Enhancement Courses 0 0 0 0 0.00 View
Social and Information Network Analysis (UG) Specialisation Elective Courses 2 0 0 0 3.00 View
Building Data Visualization for A.I. (UG) Specialisation Elective Courses 2 0 2 0 3.00 View
Gaming & Virtual Reality (UG) Specialisation Elective Courses 3 0 2 0 4.00 View
Multi Agent Systems (UG) Specialisation Elective Courses 3 0 0 0 4.00 View
Soft Computing and Applications (UG) Specialisation Elective Courses 2 0 2 0 3.00 View
Information Retrieval (UG) Specialisation Elective Courses 2 0 0 0 3.00 View
Cloud Computing Practitioner (UG) Industry Specific Courses 2 0 2 0 4.00 View
In-House Practical Training (UG) Non Teaching Credit Courses 0 0 0 0 2.00 View

Semester 6

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Introduction to Deep Learning (UG) Core Courses 2 0 2 0 3.00 View
Principles of Robot Autonomy (UG) Core Courses 3 0 0 0 3.00 View
Internet of Things: Sensing and Actuator Devices (UG) Core Courses 0 0 0 0 0.00 View
Big Data Analytics (UG) Core Courses 3 1 0 0 4.00 View
AI Tools (UG) Specialisation Elective Courses 2 0 2 0 3.00 View
Software Engineering (UG) Specialisation Elective Courses 3 1 2 0 5.00 View
Optimization Methods (UG) Specialisation Elective Courses 3 0 2 0 4.00 View
Programming & Employability Skills for Computer Engineers (UG) Employability & Skill Enhancement Courses 0 0 0 0 0.00 View
Cyber Security (UG) Specialisation Elective Courses 0 0 0 0 0.00 View
Cognitive Modelling (UG) Specialisation Elective Courses 3 0 0 0 4.00 View

Semester 7

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Language Analytics & Modelling Techniques (UG) Specialisation Elective Courses 2 0 2 0 3.00 View
Reinforcement Learning (UG) Specialisation Elective Courses 3 0 2 0 4.00 View
Natural Language Processing with Deep Learning (UG) Specialisation Elective Courses 2 0 2 0 3.00 View
A.I. in Autonomous Vehicles (UG) Specialisation Elective Courses 3 0 2 0 4.00 View
Conversational A.I. (UG) Specialisation Elective Courses 2 0 2 0 3.00 View
Time Series Analysis for AI (UG) Specialisation Elective Courses 3 0 2 0 5.00 View
A.I. in Healthcare (UG) Specialisation Elective Courses 3 0 2 0 4.00 View
Advanced Robotic Process Automation (UG) Specialisation Elective Courses 3 0 0 0 4.00 View
Recommender System (UG) Specialisation Elective Courses 3 0 2 0 4.00 View
Machine learning with graphs (UG) Specialisation Elective Courses 3 0 2 0 4.00 View
Algorithms for Computational Biology (UG) Specialisation Elective Courses 3 0 2 0 4.00 View
Digital Image Processing and Computer Vision (UG) Specialisation Elective Courses 3 1 2 0 5.00 View
Industry Internship (UG) Non Teaching Credit Courses 0 0 0 0 2.00 View
Economics for Engineers (UG) Human Social Sciences & Management Courses 2 0 0 0 2.00 View
Aspects of Indian History for Engineers (UG) Human Social Sciences & Management Courses 1 0 0 0 1.00 View
Law for Engineers (UG) Human Social Sciences & Management Courses 2 0 0 0 2.00 View
Sociology for Engineers (UG) Human Social Sciences & Management Courses 1 0 0 0 1.00 View
Minor Project (UG) Mandatory Courses 0 0 0 0 4.00 View

Semester 8

Course Title Course Type Credit L T PS SW Total Credits Syllabus
Major Project (UG) Non Teaching Credit Courses 0 0 0 0 10.00 View

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