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B.E in Artificial Intelligence and Machine Learning

Empowering Minds to Build the Next Generation of Smart Technologies.

Program Overview

The AI & ML program is designed to build expertise in artificial intelligence, machine learning, and smart technologies. It covers key areas such as neural networks, deep learning, robotics, and autonomous systems — giving students the skills to solve complex, real-world technological challenges.

The curriculum balances strong theoretical foundations with hands-on experience using modern AI frameworks and automation tools. With a focus on innovation and industry relevance, students graduate ready to design and implement AI-driven solutions that shape the future of technology.

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Program Outcomes (POs)

Graduates of AI and ML program will demonstrate the capability to:

PO1: Architect intelligent systems using advanced machine learning algorithms and data-driven methods.
PO2: Design and optimize deep learning models for advanced analysis of large-scale, complex datasets.
PO3: Build innovative applications in computer vision and NLP to enable intelligent human–machine interaction.
PO4: Integrate AI into robotics, automation, and predictive analytics to solve real-world challenges.
PO5: Adhere to ethical, transparent, and responsible AI practices to build trustworthy and socially responsible systems.

Certifications in Year 1

Build in-demand skills from Day 1 and stay ahead in your engineering journey.

1. IOT
Internet of Things

2. AI & ML
Introduction

3. Data Analytics

4. Certification in Networking

5. Design Thinking

6. MS Excel

Engineering Experience

Beyond the classroom, we ensure hands-on exposure therough real-world challenges.

Program Structure

Year 1 – Engineering Foundations

Students build strong analytical and programming skills.

Subjects include:

Engineering Mathematics
Engineering Physics / Chemistry
Programming for Problem Solving
Engineering Graphics
Environmental Studies

Year 2 – Core Computer Science

Students learn the computing fundamentals required for AI development.

Subjects include:

Data Structures and Algorithms
Object-Oriented Programming
Discrete Mathematics
Computer Organization
Database Systems

Year 3 – Artificial Intelligence Core

Students begin specialization in intelligent systems.

Subjects include:
Artificial Intelligence
Machine Learning
Data Mining
Probability and Statistics for AI
Natural Language Processing

Year 4 – Advanced AI Technologies

Students explore advanced applications of AI.

Subjects may include:

Deep Learning
Computer Vision
Robotics and Intelligent Systems
Reinforcement Learning

Students complete:

Industry Internship
Capstone AI Project

Career Outcomes

Graduates are equipped for high-impact roles in technological innovation, such as:

AI Engineer
Machine Learning Engineer
Robotics Engineer
Data Scientist
Automation Engineer

Equipped with expertise in intelligent systems and advanced analytics, graduates can excel across robotics, healthcare tech, autonomous systems, finance, and smart manufacturing—driving innovation in automation.

FAQs

What is the difference between AI and Machine Learning?

Artificial Intelligence focuses on building intelligent systems, while Machine Learning focuses on algorithms that enable systems to learn from data.

Are students trained in AI frameworks and tools?

Yes. Students gain experience with AI development tools, machine learning libraries, and data analytics frameworks.