5-Day Instructor-Led Programme
Advanced training on operationalising machine learning models with reliable deployment and monitoring practices. Learn MLOps workflows including model packaging, drift detection, and production-ready AI systems.
Duration
5 Days
Price
$2,503
Operationalising machine learning models in production requires robust engineering practices that ensure reliability, scalability, and maintainability. This programme prepares engineers to design and implement end-to-end MLOps pipelines for deploying and managing machine learning systems.
Participants learn how to package models, automate deployment pipelines, monitor performance, and detect model drift in real-world environments. The course emphasises building resilient AI systems with strong observability, incident response playbooks, and continuous delivery workflows.
Through hands-on labs, learners implement production-grade MLOps pipelines and gain experience managing the full lifecycle of machine learning models from development to deployment and monitoring.
Participants build an end-to-end MLOps pipeline including model packaging, deployment, monitoring, and drift detection.
Industry mentors guide learners through production MLOps architectures used in enterprise AI platforms.
Develop advanced skills required to manage and scale machine learning systems in production environments.
Design and implement end-to-end MLOps pipelines
Package and deploy machine learning models into production
Monitor model performance and system health
Detect and handle model and data drift
Implement incident response and recovery strategies
Build reliable and scalable AI deployment systems
Strong programming knowledge (Python recommended)
Familiarity with machine learning concepts
Basic understanding of cloud platforms or DevOps practices helpful
Organized by professional domains with comprehensive coverage
Master these in-demand skills through hands-on practice
A clear view of the roles this programme supports, what typically comes next, and where learners progress over time
Choose the learning format that works best for you and your team
Instructor-Led Training
Join live instructor-led sessions from anywhere. Interactive, engaging, and flexible.
Price per person
Group enrolments and early planning options available.
All prices are exclusive of VAT where applicable. Group enrolments and custom packages available on request.
Not everyone learns best in a group. If you want focused guidance, faster clarity, and confidence you can use on the job, our 1-to-1 Fast-Track Training gives you private, mentor-led support tailored to your experience and goals.
"Many learners choose 1-to-1 when they want understanding, not memorisation."
Everything you need to know about the certification exams
You will receive an Xcademia certificate of completion based on participation and successful completion of labs and scenario simulations.
Credential
On successful completion of MLOps Engineer, learners receive an Xcademia Certificate of Completion. This standalone certificate is issued directly by Xcademia and is aligned with globally recognised frameworks and best practices.
Everything you need to know about this course
MLOps is the practice of managing the lifecycle of machine learning models including deployment, monitoring, and maintenance.
Take the next step in your professional development
