AI & Machine Learning

Leading innovation in artificial intelligence and machine learning with cutting-edge research and industry applications

AI & Machine Learning Department

NBA Accreditation

The AI & Machine Learning programme is accredited by the National Board of Accreditation (NBA), recognizing its commitment to academic excellence, outcome-based education, and continuous quality improvement.


About the Department

CSE (Artificial Intelligence and Machine Learning (AIML) are the demanded technologies in the industry for design and development of intelligent systems. This programme is intended at studying, designing, developing, implementing, support & management of computer-based information systems. This specialization will enable the student to design and develop various intelligent systems with cutting edge technology courses viz., artificial intelligence, machine learning, computer vision, robotics, mobile application development & natural language processing etc.

Vision

To emerge as a premier department in Artificial Intelligence and Machine Learning by delivering quality technical education, fostering innovation, research, and ethical values.

Mission
  • M1: To provide a conducive learning environment for Artificial Intelligence and Machine Learning education through state-of-the-art infrastructure, advanced laboratories, and innovative teaching–learning systems.
  • M2: To produce skilled Artificial Intelligence and Machine Learning engineers with strong employability skills, leadership qualities, effective communication, social responsibility, and high ethical values.
  • M3: To provide holistic Artificial Intelligence and Machine Learning environment that fosters scientific temper, ethical values, teamwork, and professional competence among students.
  • M4: To promote quality research and innovation in Artificial Intelligence and Machine Learning by solving real-world industrial and societal problems using interdisciplinary approaches and emerging technologies.

PEO1: Technical and Leadership Competence

Apply strong foundations in Artificial Intelligence, Machine Learning, and engineering principles to solve real-world problems, demonstrating technical expertise and leadership abilities.

PEO2: Research and Innovation

Engage in cutting-edge research and development in AI and ML to create innovative solutions addressing industrial and socially relevant challenges.

PEO3: Professional and Lifelong Learning Skills

Work effectively in professional and multidisciplinary environments by exhibiting teamwork, ethical conduct, adaptability, and a commitment to continuous learning.

PO1: Engineering Knowledge

Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in WK1 to WK4 respectively to develop to the solution of complex engineering problems.

PO2: Problem Analysis

Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions with consideration for sustainable development. (WK1 to WK4)

PO3: Design/Development of Solutions

Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for the public health and safety, whole-life cost, net zero carbon, culture, society and environment as required. (WK5)

PO4: Conduct Investigations of Complex Problems

Conduct investigations of complex engineering problems using research-based knowledge including design of experiments, modelling, analysis & interpretation of data to provide valid conclusions. (WK8)

PO5: Engineering Tool Usage

Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling recognizing their limitations to solve complex engineering problems. (WK2 and WK6)

PO6: The Engineer and The World

Analyze and evaluate societal and environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture and environment. (WK1, WK5, and WK7)

PO7: Ethics

Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws. (WK9)

PO8: Individual and Collaborative Teamwork

Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.

PO9: Communication

Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences

PO10: Project Management and Finance

Apply knowledge and understanding of engineering management principles and economic decision-making and apply these to one's own work, as a member and leader in a team, and to manage projects and in multidisciplinary environments.

PO11: Life-Long Learning

Recognize the need for, and have the preparation and ability for i) independent and life-long learning ii) adaptability tone and emerging technologies and iii) critical thinking in the broadest context of technological change. (WK8)

Upon successful completion of the B.E CSE[AI&ML] programme, graduates will have:

PSO1: Technical Skill

Exhibit strong programming, modeling, and system design skills to develop intelligent AI and ML–based solutions using modern tools and emerging technologies. (Mapped to PO1, PO3, PO5)

PSO2: Theoretical Knowledge

Apply a strong theoretical foundation in mathematics, statistics, data science, and AI/ML algorithms to analyze complex problems and support research-oriented solution development. (Mapped to PO1, PO2, PO4)

PSO3: Multidisciplinary Application Development

Design and deploy AI/ML applications in multidisciplinary domains by addressing societal, ethical, environmental, and sustainability considerations through teamwork and effective communication. (Mapped to PO6, PO7, PO8, PO9, PO10)

4 Years

Program Duration

120

Annual Intake

96%+

Placement Rate

AICTE

Approved

Academic Curriculum

Our AI & Machine Learning curriculum provides comprehensive knowledge in artificial intelligence, machine learning, data science, and deep learning with hands-on project experience.

Download Curriculum Documents

Curriculum and Syllabus 2023

Our Faculty Team

Our AI & Machine Learning department comprises highly qualified faculty members with doctoral degrees, research expertise, and industry experience in artificial intelligence and data science.

Mrs.P.V.JOTHIKANTHAM

Head of the Department

M.E.,

K.S.KEERTHIKA

Assistant Professor

M.E.,

V. RAJ KUMAR

Assistant Professor

M.E.,

P.SRILEGA

Assistant Professor

M.E.,

T.JINCY

Assistant Professor

M.E.,

E.ANITHA

Assistant Professor

M.E.,

E.RENUGA

Assistant Professor

M.E.,

T.K.SUBRAMANIAM

Assistant Professor

M.E.,

Faculty Achievements
  • Published 100+ research papers in AI/ML journals and conferences
  • Research grants from DST, SERB, and industry partners
  • Patent filings in AI and machine learning innovations
  • Industry consultancy projects with leading tech companies
  • Faculty members serving as reviewers for international journals

Department Facilities

AI & Machine Learning Laboratory
  • High-performance GPU computing systems for deep learning
  • Latest AI software frameworks: TensorFlow, PyTorch, Keras
  • Cloud computing access (AWS, Google Cloud, Azure) for AI projects
  • Big data processing tools: Hadoop, Spark
  • Comfortable computing environment with 60 high-end systems
Data Science Laboratory

Our dedicated data science lab provides hands-on training in:

  • Statistical analysis and data visualization tools
  • Python and R programming environments
  • Real-time data processing and streaming analytics
  • Database systems and data warehousing
AI Innovation Center

Advanced innovation center for AI research and development:

  • AI prototyping and experimentation space
  • Robotics and IoT integration facilities
  • AR/VR development stations
  • Industry collaboration project workspace
Software and AI Tools
AI/ML Frameworks:
  • TensorFlow & Keras
  • PyTorch
  • Scikit-learn
  • OpenCV
  • NLTK & spaCy
Development Tools:
  • Jupyter Notebooks
  • Google Colab
  • Anaconda Distribution
  • Docker & Kubernetes
  • GitHub & GitLab
Cloud Computing Resources

Cloud platform access for AI development:

  • AWS Educate accounts with AI/ML services
  • Google Cloud Platform free tier access
  • Microsoft Azure for AI students
  • IBM Cloud and Watson AI services
  • High-performance computing clusters
Research and Development

Our department is actively engaged in cutting-edge AI research, focusing on emerging technologies, innovative applications, and industry collaborations to solve real-world challenges.

Research Areas
  • Deep Learning and Neural Networks
  • Computer Vision and Image Processing
  • Reinforcement Learning
  • Big Data Analytics
  • AI in Healthcare and Medicine
Research Achievements
  • Published 120+ research papers in international journals
  • Received funding from DST, SERC, and industry partners
  • 3 patents filed in AI innovations
  • Organized 5 international AI conferences
  • 25+ PhD scholars pursuing advanced AI research
Student Research

Students actively participate in:

  • AI research projects with faculty mentors
  • Kaggle competitions and hackathons
  • AI conferences and paper presentations
  • Startup and entrepreneurship initiatives
Industry Collaboration

Strategic partnerships with leading organizations:

  • IBM Watson AI Academic Initiative
  • Google AI Research Collaboration
  • Microsoft AI Development Program
  • Local AI startups for internships
Current Research Projects
Academic Projects:
  • AI-powered medical diagnosis system
  • Autonomous drone navigation
  • Sentiment analysis for social media
  • Predictive maintenance for industries
Industry Projects:
  • Chatbot development for customer service
  • Fraud detection using machine learning
  • Recommendation systems for e-commerce
  • Computer vision for quality control

Department Activities

Student Clubs and Societies
  • AI & ML Club – Weekly meetups, project showcases, and AI discussions
  • Coding Club – AI-focused programming challenges and hackathons
  • Innovation Club – AI startup ideation and product development
  • Data Analytics Club – Data science competitions and projects
Industry Interactions
  • Regular guest lectures by AI industry experts
  • Industrial visits to AI research centers and tech companies
  • Industry-sponsored AI projects and internships
  • AI startup mentorship and incubation programs
  • Alumni network in AI industry
Workshops and Training
  • Deep Learning with TensorFlow and PyTorch
  • Computer Vision and Image Processing
  • Natural Language Processing and Text Analytics
  • Big Data and Cloud Computing for AI
  • AI Ethics and Responsible AI Development
  • Research Paper Writing and Publication
Social Initiatives
  • AI awareness programs in schools
  • AI solutions for local community problems
  • Free AI workshops for underprivileged students
  • AI for social good projects

Ready to Join AI & Machine Learning Program?

Take the first step towards an exciting career in artificial intelligence and machine learning. Contact our department for more information about the program and admission process.