Operationalizing ML Models: MLOps for Scalable AI
Master MLOps to deploy, scale, and maintain ML models efficiently. Learn to build scalable workflows, set up CI/CD pipelines, monitor performance, and optimize AI infrastructure for real-world impact!
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Course Overview
Ready to take your machine learning models from concept to real-world impact? This course is your gateway to mastering MLOps (Machine Learning Operations)—the essential skill set for deploying, scaling, and maintaining machine learning models effectively in production.
MLOps is all about ensuring your models run smoothly and efficiently, solving real-world challenges along the way. You’ll learn how to tackle performance issues before they escalate, create automated pipelines that make updates seamless, and establish best practices for managing AI infrastructure.
Skills You Will Gain
Course Includes
This course includes:
- On-demand videos
- Practice assessments
- Multiple hands-on learning activities
- Exposure to a real-world project
- 100% self-paced learning opportunities
- Certification of completion
Learning Outcomes (At the end of this program, you will be able to...)
- Implement scalable MLOps workflows that ensure efficient and reliable machine learning operations.
- Build CI/CD pipelines for seamless and automated model updates, streamlining the development lifecycle.
- Monitor deployed ML models for performance and drift.
- Optimize AI infrastructure to handle scalability challenges and support high-performance deployments.
Prerequisites
To get the most out of this course, you should have a basic understanding of machine learning concepts, familiarity with Python programming, and some experience with Docker and containerization. These prerequisites will provide a solid foundation, allowing you to focus on the advanced MLOps techniques covered in the course. If you're comfortable with these areas, you'll be well-equipped to dive into real-world applications of MLOps and enhance your machine learning workflows.
Who Should Attend
This course is perfect for Data Scientists, Machine Learning Engineers, AI Practitioners, and IT Professionals managing AI systems. Whether you're building models, deploying them in production, or overseeing AI infrastructure, mastering MLOps will equip you with the essential skills to streamline operations, ensure model performance, and optimize workflows. You'll gain hands-on experience in managing end-to-end machine learning pipelines, handling real-world challenges, and ensuring scalability and efficiency across AI systems.
Curriculum
Explore the comprehensive, hands-on curriculum designed to build your expertise step by step.
Meet Your Expert Instructors
Luca Berton
VIEW MY CHANNELFrequently Asked Questions
How much do the courses at Starweaver cost?
We offer flexible payment options to make learning accessible for everyone. With our Pay-As-You-Go plan, you can pay for each course individually. Alternatively, our Subscription-Based plan provides you with unlimited access to all courses for a monthly or yearly fee.
Do you offer any certifications upon completion of a course at Starweaver?
Yes, we do offer a certification upon completion of our course to showcase your newly acquired skills and expertise.
Does Starweaver offer any free courses or trials?
No, we don't offer any free courses, but we do offer 5-day trial only on our subscriptions-based plans.
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Our course is designed with three levels to cater to your learning needs - Core, Intermediate, and Advanced. You can choose the level that best suits your knowledge and skillset to enhance your learning experience.
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Do you offer refunds?
Yes, we do offer a 100% refund guarantee for our courses within a specified time frame. If you are not satisfied with the course, contact our customer support team to request a refund with your order details. Some restrictions may apply.
