The central idea
DeployAI 2026 is an intensive 14-day winter school designed to bridge the gap between learning artificial intelligence concepts and deploying reliable, scalable, and responsible AI systems in real-world environments.
The complete lifecycle
The programme covers the complete AI lifecycle, beginning with the foundations of machine learning and deep learning and progressing toward foundation models, large language models, MLOps, cloud-native deployment, responsible AI, and end-to-end AI application development.
How you will learn
Through expert-led sessions, guided laboratories, industry-oriented case studies, deployment exercises, collaborative activities, and a final capstone project, participants will gain both theoretical understanding and practical experience in building production-ready AI solutions.
Meet your hosts
IIT Ropar is an Institute of National Importance in Rupnagar, Punjab. Its main campus brings together lecture halls, computing labs, project spaces, hostels, dining, sports, a library, and medical support.
DeployAI 2026 sessions will use campus facilities for lectures, practical labs, mentoring, and project demonstrations. Follow the room allocations shared by the organisers.
The School of Artificial Intelligence and Data Engineering (sAIDE) at IIT Ropar brings together education and research in AI and data engineering. Its research spans computer vision, digital agriculture, healthcare, robotics, security and speech technology.
The school organises DeployAI 2026 to connect AI foundations with practical system development and deployment.
One connected experience
Build strong foundations in machine learning, deep learning, and modern AI architectures.
Gain practical exposure to foundation models and large language models, including how they are used in modern AI systems.
Learn how to build complete AI applications, from data preparation and model development through integration and deployment.
Gain hands-on experience with MLOps pipelines, model monitoring, deployment workflows, and lifecycle management for reliable AI systems.
Develop practical skills with cloud-native tools, containers, APIs, and scalable deployment practices for production AI systems.
Understand responsible AI principles including model reliability, safety, fairness, ethical deployment, and trustworthy AI system design.
Explore industry-oriented case studies that connect academic AI concepts with practical deployment challenges and real-world requirements.
Participate in guided laboratory sessions, deployment exercises, and collaborative problem-solving activities designed to reinforce practical AI skills.
Interact with academic experts, researchers, and industry professionals to gain broader perspectives on AI research, engineering, and deployment.
Design, develop, and deploy a complete AI solution as a final capstone project that brings together the concepts, tools, and deployment practices covered throughout the programme.
