DevOps & MLOps Self-Paced in Riyadh

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This comprehensive DevOps course will equip you with the essential skills to bridge the gap between development and IT operations, ensuring faster and more reliable software delivery.

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Overview

✅ What You'll Learn:

✔ CI/CD Pipelines – Automate code integration & deployment using Jenkins, GitHub Actions, and GitLab CI/CD.
✔ Containerization & Orchestration – Learn Docker & Kubernetes for scalable, cloud-native applications.
✔ Infrastructure as Code (IaC) – Manage infrastructure with Terraform & Ansible.
✔ Cloud Computing – Deploy applications on AWS, Azure, or Google Cloud.
✔ Monitoring & Logging – Use Prometheus, Grafana, and ELK Stack for real-time system monitoring.
✔ Security & Compliance – Implement DevSecOps practices for secure deployments.

What are the Takeaways?

Understand DevOps Principles – Learn CI/CD, Infrastructure as Code (IaC), automation, and cloud deployment strategies.
Deploy ML Models at Scale – Use Docker & Kubernetes to serve models in production environments.
Monitor Model Performance – Implement real-time monitoring of ML models to track performance drift.
Integrate ML with CI/CD Pipelines – Automate retraining and deployment of models with DevOps practices.
Optimize ML Model Serving – Use TensorFlow Serving, FastAPI, or AWS SageMaker for efficient model hosting.

Who Should Attend?

Software Developers & Engineers – Looking to streamline deployments, automate workflows, and integrate DevOps practices.
Machine Learning Engineers & Data Scientists – Wanting to deploy, monitor, and scale ML models efficiently using MLOps.
DevOps & Cloud Engineers – Seeking expertise in CI/CD, Kubernetes, Infrastructure as Code (IaC), and cloud deployments.
System Administrators & IT Professionals – Interested in automating infrastructure, managing cloud environments, and improving deployment processes.
AI & ML Enthusiasts – Looking to break into MLOps by learning real-world model deployment strategies.