Website Deployment Courses and Certifications

Whizlabs

Azure AI & ML: Optimize Language Models for AI Applications

Master Azure AI & ML model deployment, optimization, and MLOps workflows. Build production-ready solutions using Azure AI Foundry, AutoML, and advanced monitoring techniques.

• Coursera
• 8 hours 19 minutes
• Self-Paced
• Paid Course

Whizlabs

Azure ML: Deploying, Managing, and Experimenting with Models

Master Azure ML model deployment, management, and experimentation with MLOps best practices, AutoML, and Responsible AI implementation for scalable machine learning workflows.

• Coursera
• 7 hours 44 minutes
• Self-Paced
• Paid Course

Scrimba

Deploy a Website with Netlify

Deploy web projects seamlessly with Netlify. Learn step-by-step methods for various applications, from simple JavaScript to advanced React and Next.js setups. Gain practical skills for efficient deployment.

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

Coursera Career Certificate

Gradient to Production: MLOps & Model Serving

Master the full MLOps stack—from data pipelines to model deployment—using FastAPI, Docker, Kubernetes, and Airflow, and learn to ship, monitor, and maintain ML systems in production.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 15 courses

Coursera

Optimizing and Deploying Computer Vision Models

Explore techniques to optimize and deploy computer vision models, covering dataset analysis, augmentation, model evaluation, training stability, and reproducible AI workflows for real-world applications.

• Coursera
• 7 hours 18 minutes
• Self-Paced
• Paid Course

Packt

Vibe Coding with Windsurf – No Code Web Design

Master no-code web design using AI tools like Windsurf to create professional websites without coding skills, from concept to live deployment.

• Coursera
• 4 hours 27 minutes
• Self-Paced
• Paid Course

Coursera

MLOps in R: Deploying machine learning models using vetiver

Learn to deploy machine learning models efficiently using Vetiver in R. Build ensemble models, set up deployment frameworks, and monitor performance through a hospital readmission scenario.

• Coursera
• 2 hours 39 minutes
• Self-Paced
• Paid Course

Coursera

GPU Clusters & Containers

Unlock distributed AI training and production deployment using cloud GPU clusters and containerization strategies for scalable machine learning systems.

• Coursera
• 2 hours 5 minutes
• Self-Paced
• Paid Course

Deploy Your Website on Cloud Run

This is a self-paced lab that takes place in the Google Cloud console. In this lab you will deploy a website to Google Kubernetes Engine, scale it out to more instances, then deploy a new version using rolling updates.

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

Deploy and Scale AI Models with Cloud Run

Discover how to deploy and optimize AI inference services on Cloud Run with GPU support and data storage integration for efficient serverless ML applications.

• Coursera
• 1 hour 24 minutes
• Self-Paced
• Paid Course

Packt

Databricks ML in Action

Master practical machine learning on Databricks platform with hands-on projects covering MLflow, Vector Search, AutoML, and complete ML lifecycle from data ingestion to deployment.

• Coursera
• 13 hours 23 minutes
• Self-Paced
• Paid Course

KodeKloud

Deploy ML Models to Production

Master MLOps by deploying ML models from development to production using MLflow, BentoML, and AWS SageMaker with hands-on insurance claim application project.

• Coursera
• 3 hours 53 minutes
• Self-Paced
• Paid Course

Deploy, Scale, and Update Your Website on Google Kubernetes Engine

This is a self-paced lab that takes place in the Google Cloud console. In this lab you will learn how to deploy a website to Google Kubernetes Engine, scale it out to more instances, and deploy a new version using Rolling Updates.

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

Managing Machine Learning Models

Master model lifecycle management from creation to deployment, including governance, testing, monitoring, and automated scoring across SAS, Python, and R environments.

• Coursera
• 8 hours 34 minutes
• Self-Paced
• Paid Course

H2O.ai

Data Science and Machine Learning H2O.ai Platforms

Master H2O.ai's comprehensive data science toolkit for automated machine learning, model deployment, and generative AI applications, featuring Driverless AI, Wave App, and Enterprise GPTe.

• Coursera
• 1 hour 12 minutes
• Self-Paced
• Paid Course