Last Updated:
LIVE TRAINING · MENTOR-LED PROJECTS
Cover experiment tracking, feature pipelines, model registry, ML delivery, scalable serving, monitoring and controlled releases.
EXAMPLE PROJECT BRIEF
Use this example to discuss the project scope for this specialist module with your mentor.
What to demonstrate: Show a passing pipeline, a failed deployment check, and the logs used to troubleshoot the service.
This MLOps specialist course follows the model lifecycle through experiment tracking, data validation, feature pipelines, versioning, CI/CD, serving, Kubeflow pipelines, monitoring, drift detection and staged deployment patterns.
Learn to build, deploy and support customer-facing AI systems as an enterprise AI engineer.
YOU + FOUR FRIENDS
Bring four friends or colleagues and ask about BAIC’s reduced fee for a group of five learners.
We’ll confirm your course’s eligibility, group fee, schedule and final payable amount before you enrol.
Ask about the group fee ↗A role-aware transition plan that turns your current engineering or data experience into credible AI work.
YOU + FOUR FRIENDS
Bring four friends or colleagues and ask about BAIC’s reduced fee for a group of five learners.
We’ll confirm your course’s eligibility, group fee, schedule and final payable amount before you enrol.
Ask about the group fee ↗Ship AI features inside real products: LLM APIs, agents, evals and production patterns.
YOU + FOUR FRIENDS
Bring four friends or colleagues and ask about BAIC’s reduced fee for a group of five learners.
We’ll confirm your course’s eligibility, group fee, schedule and final payable amount before you enrol.
Ask about the group fee ↗Book a free introductory call. We will discuss your background, the syllabus and whether this is the right starting point.
Share your details. A course adviser will help you choose a course and explain the fees and batch dates.
Leave your details and a course adviser will contact you about group training.
Ask a course advisor for the current batch fee, payment details and what is included before enrolling.
Ask a course advisor for the teaching hours, weekly timetable and project scope for the next batch.
This MLOps specialist course follows the model lifecycle through experiment tracking, data validation, feature pipelines, versioning, CI/CD, serving, Kubeflow pipelines, monitoring, drift detection and staged deployment patterns.
Gaurav S — Lead FDE, working with multinational clients (15 years of IT experience; previously at HCL, Accenture, HP and Wipro)
Ask about project feedback, the teaching approach and the support available for your course.
View Gaurav’s profile →