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Cloud Engineering, DevOps & AI Operations
Join Cloud Engineering, DevOps & AI Operations by MAB - a practical training program for focused digital growth.
Led by experienced trainers, master AI workflows, practical implementation, freelancing direction, and modern digital systems. Gain expert insights to transform your career.
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Cloud Engineering, DevOps & AI Operations: Training Content, Bonuses & Career Direction
Whats New:-
- AI Workflows
- Automation Systems
- Client Projects
- Portfolio Direction
Course Outline:-
AWS core services: EC2, S3, RDS, Lambda, and IAM:
Cloud Fundamentals: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
GCP and Azure equivalents for cross-cloud literacy:
Cloud Fundamentals: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Networking: VPC, subnets, and security groups:
Cloud Fundamentals: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Cloud cost management and resource tagging:
Cloud Fundamentals: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Writing optimized Dockerfiles and multi-stage builds:
Docker & Containerization: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Docker Compose for local multi-service development:
Docker & Containerization: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Container registry workflows with ECR and GCR:
Docker & Containerization: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Security scanning and image hardening:
Docker & Containerization: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Pods, deployments, services, and ingress controllers:
Kubernetes & Orchestration: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Helm charts and package management:
Kubernetes & Orchestration: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Auto-scaling and resource limits:
Kubernetes & Orchestration: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Kubernetes on EKS, GKE, and AKS:
Kubernetes & Orchestration: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Terraform modules, state management, and workspaces:
Infrastructure as Code with Terraform: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Provisioning cloud resources declaratively:
Infrastructure as Code with Terraform: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
CI/CD integration for infrastructure changes:
Infrastructure as Code with Terraform: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
GitHub Actions and GitLab CI pipeline design:
CI/CD Pipelines: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Blue-green and canary deployment strategies:
CI/CD Pipelines: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Secrets management with Vault and cloud KMS:
CI/CD Pipelines: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Automated testing gates in deployment pipelines:
CI/CD Pipelines: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Model registry, versioning, and artifact storage:
MLOps & AI Operations: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Serving AI models with Triton and BentoML:
MLOps & AI Operations: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Monitoring model drift and performance degradation:
MLOps & AI Operations: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Retraining pipelines with Kubeflow and Airflow:
MLOps & AI Operations: practical training, examples, and implementation tasks for Cloud Engineering, DevOps & AI Operations.
Portfolio and Client-Ready Execution:
Build practical assets you can show to clients, employers, or partners.
Tools, Systems, and Automation:
Use modern software, AI workflows, and repeatable systems to save time and improve delivery quality.
Growth and Monetization:
Learn how to turn your new skills into services, products, campaigns, or income opportunities.
Get Enrolled Now
Learn the core principles of Cloud Engineering, DevOps & AI Operations. Build standout projects, implement practical systems, and gain the skills necessary to move forward in the digital landscape.
AI
Rs. 60,000
Important Note
- No registration fee
- One-time fee only
- Live lectures
- Recorded lectures
- Lifetime learning access
- No monthly subscription
Course Access
- Student portal access
- Web, iOS, and Android access
- Private learning community
- Course updates
Training Content
- Module 1: Cloud Fundamentals
- Module 2: Docker & Containerization
- Module 3: Kubernetes & Orchestration
- Module 4: Infrastructure as Code with Terraform
- Module 5: CI/CD Pipelines
- Module 6: MLOps & AI Operations
Support
- Live support
- Community help
- Q&A guidance
- Practical feedback
Resources
- Templates
- Checklists
- Tools list
- Project resources
Bonus
- Freelancing guidance
- AI workflow pack
- Portfolio direction
Our Success Stories
Meet learners who turned training into real progress. Each story is a reminder that focused learning, practice, and consistency can open strong career opportunities.
MAB Student
Earned: $3,000+
Source: Freelancing
This training gave me a clear path, practical assignments, and confidence to start offering digital services.
Frequently Asked Questions
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