Programme Overview

The Bachelor of Engineering in Artificial Intelligence and Machine Learning is dedicated to advancing the fields of artificial intelligence and machine learning through research, education, and collaboration. Its interdisciplinary team of experts includes researchers, engineers, and data scientists, all working together to develop cutting-edge algorithms and models that can solve complex problems and drive innovation in various industries. The department also offers training and educational programs to equip individuals and organizations with the skills and knowledge necessary to harness the power of AI and ML and actively collaborates with other academic and industry partners to push the boundaries of what is possible in these rapidly evolving fields. Ultimately, the Department of AI and ML is committed to creating a future where intelligent machines and algorithms work alongside humans to create a better world for all.

  • 4 Years

    Duration of programme

  • UG

    Level of Study

Key Highlights

High Configured Central Artificial Intelligence Lab
Wifi Enabled Campus
IoT & Advanced Research Lab
Smart Classrooms
High Qualified and Experienced Faculty Member

How will you benefit

Job Opportunities: With a B.E. AI & ML degree, you can access a wide range of job opportunities in various industries such as Software Development, IT Consulting, Telecommunications, and E-Commerce.
High Salary: A B.E. AI and ML degree is in high demand, and graduates often receive lucrative salary packages.
Innovation and Creativity: B.E. AI and ML programmes are designed to encourage innovation, creativity, and problem-solving skills, allowing you to develop unique solutions to real-world problems.
Career Growth: As a B.E. AI and ML graduate, you can expect excellent career growth opportunities, with options to specialise in different areas such as Artificial Intelligence, Cybersecurity, Software Engineering, and more.

What will you study

Programming languages: You may learn programming languages such as Python, R, and MATLAB, which are commonly used in AI and ML.

Optimization methods: Optimization methods are used to find the optimal solution for a problem, and you may study techniques such as gradient descent and convex optimization.

Linear algebra: Linear algebra is a branch of mathematics that deals with linear equations and matrices and is used extensively in machine learning algorithms.

Probability and statistics: Probability and statistics are fundamental to understanding the concepts of AI and ML, and you may study topics such as probability theory, hypothesis testing, and regression analysis.

  • PO1: Engineering Knowledge: Apply foundational engineering principles to solve complex problems in data science and related fields.

  • PO2: Problem Analysis: Critically analyze and solve engineering problems using advanced mathematical and scientific principles.
  • PO3: Design/Development of Solutions: Design innovative solutions that meet societal needs while considering ethical and environmental factors.
  • PO4: Conduct Investigations of Complex Problems: Conduct research and experiments to derive valid conclusions for engineering challenges.
  • PO5: NModern Tool Usage: Utilize modern engineering tools and technologies effectively for predictive modelling and analysis.
  • PO6: The Engineer and Society: Assessing societal implications and ethical responsibilities in engineering practice.
  • PO7: Individual and Team Work: Collaborate effectively within multidisciplinary teams and diverse settings.
  • PO8: Communication: Communicate engineering concepts and solutions clearly and effectively to diverse audiences.
  • PO9: Project Management and Finance: Apply engineering and management principles to successfully manage projects.
  • PO10: Life-long Learning: Recognize the importance of continuous learning and adaptability in response to technological advancements.

  • PSO1: Graduates will demonstrate proficiency in designing, implementing, and optimizing advanced algorithms and models for AI and ML applications, such as neural networks, deep learning, and reinforcement learning.
  • PSO2: Graduates will be capable of developing intelligent systems that can perceive, reason, and act autonomously or semi-autonomously, applying AI techniques to solve complex problems in various domains.
  • PSO3: Graduates will adhere to ethical principles in the development and deployment of AI systems, ensuring fairness, transparency, privacy, and accountability in AI applications, aligned with societal and legal standards.

PEO1: Graduates will demonstrate strong proficiency in AI and ML technologies, algorithms, and software development.

PEO2: Graduates will effectively apply AI and ML techniques to solve real-world challenges across various domains.
PEO3: Graduates will uphold ethical standards and consider societal impacts while developing and deploying AI systems.
PEO4: Graduates will engage in continuous learning to stay current with technological advancements and industry trends.

PEO5: Graduates will exhibit leadership and collaborative skills, working effectively in multidisciplinary teams. 

Curriculum

  • Engineering Chemistry
  • Mathematics-I
  • Engineering Graphics
  • Basic Electrical Engineering
  • Basic Computer Engineering
  • Manufacturing Practices
  • Entrepreneurship development

  • Engineering Physics
  • Mathematics-II
  • Basic Mechanical Engineering
  • Basic Civil & Engg Mechanics
  • Communication Skills
  • Health
  • Hygiene & Yoga
  • Rural Outreach

  • Mathematics-III
  • Discrete Structures
  • Programming in Java
  • Object Oriented programming & Methodology
  • Data structures
  • Computer Programming & Tools-I(HTML)
  • Skill Electives-I

  • Mathematics & Statistics for Machine Learning
  • Advance Computer Architecture
  • Analysis and Design of Algorithm
  • Python Programming
  • Operating System
  • Computer Programming and Tools
  • Skill Electives-II

  • Introduction to AI
  • Machine Learning
  • Data Base Management Systems
  • Software Engineering and Agile Methodologies
  • Web Programming Fundamentals
  • Unix and Shell Programming Lab
  • Skill Elective-III

  • Natural Language Processing
  • Deep Learning Fundamentals
  • High End Programming (Elective)
  • Computer Networking
  • Computer Vision & Image Processing
  • Report Writing using Latex
  • Skill Electives -IV

  • Robotics
  • Fundamentals of Cybersecurity
  • Cloud and Distributed Computing
  • Information Storage & Management
  • Professional Elective-I

  • Soft Computing
  • Reinforcement Learning
  • Professional Elective-II
  • Open Elective-II
  • Professional Elective-I

CAREERS AND EMPLOYABILITY

Robotics Engineer
Business Intelligence Analyst with Focus on AL
Data Scientist
AI Business Analyst

ELIGIBILITY CRITERIA

12 th in PCM with 45 %(40% in case of SC/ST)

3 year diploma in any stream

 

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Registered Office

Rabindranath Tagore University,

Mendua, Post: Bhojpur, Near - Bangrasiya chouraha, Bhopal-Chiklod Road, District: Raisen,(M.P.)

07552700401 | 07552700447 |

[email protected]

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