Continuous Deployment Courses and Certifications

Jenkins 2 Bootcamp: Fully Automate Builds to Deployment 2020

6265 ratings at Udemy

An introduction to the Jenkins build server using continuous integration and deployment techniques -- all step by step.

• Udemy
• 9 hours 1 minute
• Self-Paced
• Paid Course

Docker - Containers, Images, Compose, Kubernetes, and more!

6213 ratings at Udemy

Create Docker containers & multi-container apps. Learn Compose, Kubernetes, Nginx, Cloudflare, & more!

• Udemy
• 23 hours 18 minutes
• Self-Paced
• Paid Course

Coursera

Jenkins : Automating your delivery pipeline

342 ratings at Coursera

Build a continuous delivery pipeline in Jenkins for a Spring Pet Clinic application, applying pipeline-as-code practices in a hands-on DevOps workflow.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course

Using DevOps to Speed Up Time to Market

Faster delivery need not cost quality: use continuous integration, value stream mapping, feature flags, small-batch releases, and metrics like lead time and deployment frequency.

• Coursera
• 3 weeks, 2 hours a week
• Self-Paced
• Paid Course

Continuous Deployments using Spinnaker on AWS and Kubernetes

1985 ratings at Udemy

Use Spinnaker to execute your DevOps strategy. Use immutable infrastructure to deploy using Spinnak on AWS or Kubernetes

• Udemy
• 4 hours 36 minutes
• Self-Paced
• Paid Course

AWS CodeDeploy

1729 ratings at Udemy

Master AWS CodeDeploy, from basic code deployment use cases to advanced zero-downtime patching of your app.

• Udemy
• 4 hours 13 minutes
• Self-Paced
• Paid Course

Continuous Delivery with Jenkins in Kubernetes Engine

This is a self-paced lab that takes place in the Google Cloud console. In this lab you will deploy and completely configure a continuous delivery pipeline using Jenkins running on Kubernetes Engine and go through the dev - deploy process.

• Coursera
• 1 hour 15 minutes
• Self-Paced
• Paid Course

Scrimba

Deploy a Website with Netlify

Deploy web projects with Netlify: publish JavaScript apps by drag-and-drop and set up continuous deployment for React and Next.js sites.

• Coursera
• 45 minutes
• Self-Paced
• Paid Course

Coursera

Deploy, Evaluate and Create AI Systems

Ship AI models to production reliably: analyze Dockerfiles, SBOMs and dependency graphs, benchmark latency and cost across targets, and build blue-green zero-downtime release strategies.

• Coursera
• 3 weeks, 1 hour a week
• Self-Paced
• Paid Course

Board Infinity

Continuous Integration (CI) Insight for Agile Development

Configure CI pipelines with Jenkins, Travis CI, and CircleCI, automate tests, manage branch merges, extend to Continuous Delivery, and secure pipelines with secret management.

• Coursera
• 3 weeks, 4 hours a week
• Self-Paced
• Paid Course

Coursera

Optimize AI: Plan, Evaluate, and Learn

Plan model retraining from performance data, evaluate algorithm families under real constraints, and design continuous-learning strategies with MLflow dashboards, canary deployments, and rollback safeguards.

• Coursera
• 1 hour 50 minutes
• Self-Paced
• Paid Course

Continuous Delivery Pipelines with Spinnaker and Kubernetes Engine

This is a self-paced lab that takes place in the Google Cloud console. Create a Kubernetes Engine cluster, deploy an application, and use Spinnaker to continuously deploy the application when changes are made to the application.

• Coursera
• 1 hour 30 minutes
• Self-Paced
• Paid Course

Coursera

Orchestrate, Analyze, and Evaluate AI Deployments

Orchestrate AI deployment lifecycles with CI/CD, GitLab and Kubernetes, analyze telemetry to trace error spikes and root causes, and evaluate models against KPIs like conversion lift.

• Coursera
• 2 hours 13 minutes
• Self-Paced
• Paid Course

Scrimba

Intro to DevOps

Trace an application from local development to production through Docker, CI/CD, migrations, health checks, rollbacks, and CDN delivery.

• Coursera
• 5 weeks, 2 hours a week
• Self-Paced
• Paid Course

Coursera

Integrate and Optimize AI Services Seamlessly

Integrate AI prediction services with gRPC and protobuf, message queues and APIs, then read Prometheus metrics and judge canary releases, stabilizing or rolling back versions.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course