B.Tech in Artificial Intelligence and Machine Learning

Shaping Tomorrow’s AI Engineers Today

B. Tech in Artificial Intelligence and Machine Learning is a defined platform to learn basics and advanced programming about computers. This program nurtures aspirants having an interest in grasping computer technology from grass root to zenith. At Symbiosis University of Applied Sciences B. Tech in Artificial Intelligence and Machine Learning course, we co-create an ideal ambience for learning through real-time skill development and support from industry-experienced faculty to unlock a new tomorrow.

Applied Mathematics

Web Technology

Fundamental of Artificial Intelligence

Problem Solving and Programming Concepts
Database Management System

Data Analytics Lab

Managerial Communication Skills

IDSC – II (MOOC Course)

Data Structures

AI – Mathematical Concepts

Operating System

Natural Language Processing

Python Programming

Cognitive Development Skills

Environmental Studies

Internship – I

IDSC – II (MOOC Course)

Machine Learning

Probability and Statistics

Computer Networks

BFSI

Retail

Cloud Computing

Disaster Management

Professional Ethics

IDSC – II (MOOC Course)

Machine Learning

Computer Networking

BFSI

Retail

Big Data Analytics

Software Engineering

Robotics and Automation

Constitution of India

Entrepreneurship Development

Internship – I

IDSC – II (MOOC Course)

Reinforcement Learning

Computer Vision

Advanced Algorithms

IoT and Edge Computing

Research Methodology

BFSI

Retail

Leadership and Team Management

IDSC – II (MOOC Course)

Advanced Machine Learning

Blockchain Technology

Cyber Security

AI Ethics and Governance

BFSI Retail

Project Management

Global Business Environment

Internship – II

IDSC – II (MOOC Course)

Advanced Natural Language Processing

AI For Business Applications

Capstone Project

Organizational Skills

Six Months – Internship

Seminar

AI and ML bring powerful benefits to organizations of all shapes and sizes, with new possibilities constantly emerging. In particular, as the amount of data grows in size and complexity, automated and intelligent systems are becoming vital to helping companies automate tasks, unlock value, and generate actionable insights to achieve better outcomes.

Industries are using AI and ML in various ways to transform their work and do business. Incorporating AI and ML capabilities into their strategies and systems helps organizations rethink how they use their data and available resources, drive productivity and efficiency, enhance data-driven decision-making through predictive analytics, and improve customer and employee experiences.

Data Scientist
AI Scientist
AI/ML Research Engineer
Computer Vision Engineer

Recommendation Systems – Used by platforms like Netflix, Amazon, and YouTube to suggest content or products.
Virtual Assistants & Chatbots – AI-powered assistants like Siri, Alexa, and customer support bots.
Image & Facial Recognition – Used in security systems, smartphones, and surveillance.
Natural Language Processing (NLP) – Enables text understanding, translation, sentiment analysis, and voice recognition.
Healthcare & Diagnosis – Disease prediction, medical imaging analysis, and personalized treatment plans.
Fraud Detection – Identifies unusual patterns in banking and financial transactions.
Autonomous Vehicles – Self-driving cars and smart navigation systems.
Predictive Analytics – Forecasting trends in business, weather, sales, and demand.
Robotics & Automation – Industrial robots, process automation, and smart manufacturing.
Cybersecurity – Threat detection, anomaly detection, and network security.
Speech Recognition – Voice-to-text systems and voice command technologies.
Personalization in Marketing – Targeted ads, customer segmentation, and behavior analysis.

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Click Here - Eligibility Criteria

Comprehensive Industry Oriented Curriculum: Well-designed curriculum covering the fundamentals and advanced topics in AI and ML (Generative AI, Deep Learning, Natural Language Processing, Computer Vision, etc.)
Hands-On/ Skills: More emphasis on practical, skills hands-on approach with real-world projects.
Expert Faculty: Highly qualified and experienced faculty members with expertise in AI and ML, with significant contribution in research and industry sectors.
State-of-the-Art Labs: Well-equipped AI and ML laboratories with the latest hardware and software resources.
Interdisciplinary Approach: Collaborations with other departments to promote interdisciplinary learning, such as combining AI/ML with business, healthcare, or engineering, etc.
Industry Connections: Partnerships with leading tech companies to provide internships, workshops, and guest lectures from industry experts.
Hackathons and Technical Event: Frequent conduction of technical activities like hackathons, data science competitions, and coding challenges to foster a competitive and collaborative learning environment.
Networking Opportunities: Through various outreach programs such as Industry and International collaborative events, conferences, and seminars with professionals in AI and ML across the globe.
Career Services: Dedicated career services to assist students in securing internships and job placements in AI and ML-related fields.
Research Mentorship for Higher Education: Opportunities for students to engage in AI and ML research projects to cater their scope for pursing higher education.