MLOps

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This MLOps course helps professionals build, deploy, monitor, and automate ML models in production using tools like Docker, Kubernetes, CI/CD, and Cloud Platforms.

Introduction to MLOps

Fundamentals of Machine Learning

Version Control & Reproducibility

CI/CD for Machine Learning

Containerization & Orchestration

Model Deployment & Serving

: Monitoring & Logging

Cloud & MLOps Tools

Security & Compliance in MLOps

Final Project & Industry Best Practices

Is this course beginner-friendly?

It is recommended to have basic ML knowledge, but we cover everything step-by-step.

Will I receive a certificate?

Yes! A certificate from Scylence Computer Academy will be awarded upon successful completion.

What kind of projects will I work on?

You will build end-to-end MLOps pipelines, deploy models using Docker, Kubernetes & CI/CD, and monitor model performance.

Will this course help me get a job?

Yes! MLOps is one of the fastest-growing fields, and this course prepares you for MLOps Engineer, ML Engineer, and DevOps ML Specialist roles.

Enrollment is open throughout the year.
Limited seats available for offline classes.
Students must complete assignments and a final project for certification.

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Course details

Duration 12 Weeks

Lectures 31

Video (80+ Hours Total)

Basic info

Mode: Online/Offline
Language: Hindi, English
Certification: Provided upon successful completion
Trainer Support: Available for doubts and queries

Course requirements

Basic knowledge of Python & Machine Learning
Understanding of Linux & Cloud Fundamentals (recommended)
A computer/laptop with internet access

Intended audience

Data Scientists & ML Engineers looking to automate ML workflows
DevOps Engineers exploring MLOps & AI automation
Software Engineers interested in scalable ML deployments

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