DeployAI 2026 is planned as an intensive 14-day winter school combining expert lectures, guided tutorials, hands-on laboratories, technical discussions, mentor interaction, case studies, project development, and final demonstrations.

The programme schedule will provide participants with a structured progression from foundational artificial intelligence concepts to the deployment and operation of complete AI systems.

The programme is expected to include the following types of activities:

A typical programme day may include:

The actual timing may vary depending on the topic, invited speaker availability, laboratory requirements, project activities, and institutional arrangements.

AI landscape, AI engineering, deployable AI ecosystem, participant orientation, technical setup, and introduction to the programme.

Python for AI, data preparation, data processing, visualisation, and reproducible development environments.

Machine learning foundations, supervised learning, training workflows, and evaluation metrics.

Feature engineering, model selection, validation, error analysis, and machine learning pipelines.

Deep learning foundations, neural networks, optimisation, and model training using modern frameworks.

Computer vision, image representation, classification, visual recognition, and deployment-oriented workflows.

Natural language processing, text representation, classification, sequence modelling, and practical language applications.

Foundation models, generative AI, pretrained models, adaptation methods, and responsible use.

Large language models, prompt engineering, application design, evaluation, and safety considerations.

Retrieval-Augmented Generation, embeddings, vector databases, document processing, and knowledge-grounded applications.

MLOps, experiment tracking, dataset and model versioning, reproducibility, testing, and automation.

Model serving, API development, inference pipelines, latency, scalability, and production integration.

Docker, cloud deployment, monitoring, security, responsible AI, and maintenance of deployed systems.

Capstone project, hackathon completion, end-to-end deployment, technical demonstration, evaluation, feedback, and closing session.

The final schedule will include:

The detailed session-wise schedule will be added through the Schedule management section of the microsite admin panel.

The organising committee may revise session timings, speakers, venues, laboratories, or activity order when necessary.

All important updates will be communicated through the event website, registered email address, or official event communication channels.

Participants should check the latest schedule before each programme day and follow the instructions issued by the organising team.

Participants are expected to attend all required lectures, laboratories, project sessions, mentor interactions, and demonstrations.

Minimum attendance, assignment completion, project participation, or evaluation requirements may apply for certificate eligibility.

Participants are required to bring their own laptop, charger, and any necessary accessories to all practical sessions.

Software installation, datasets, account creation, development environments, and other technical preparation instructions may be shared before the programme.

Participants should complete the required setup within the communicated deadline to avoid delays during laboratory sessions.