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Scylence Academy
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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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