Model Deployment Courses and Certifications

Coursera Credential

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

Packt

Real-world End to End Machine Learning Ops on Google Cloud

Master the complete ML lifecycle on Google Cloud with CI/CD pipelines, Vertex AI, Kubeflow, and automated deployment using real-world hands-on projects and industry best practices.

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

Practical Machine Learning without Coding

Discover how to build, optimize, and deploy machine learning models using no-code platforms, from standard algorithms to advanced automation and real-world business integration.

• Coursera
• 3 hours 20 minutes
• Self-Paced
• Paid Course

Coursera

Optimize AI: Build Reusable Model Pipelines

Master strategic model selection and build standardized ML pipelines using Scikit-learn for efficient, scalable AI workflows in production environments.

• Coursera
• 1 hour 47 minutes
• Self-Paced
• Paid Course

Coursera

Orchestrate, Analyze, and Evaluate AI Deployments

Master MLOps deployment lifecycle with CI/CD, Kubernetes, and GitLab. Analyze telemetry data, troubleshoot performance issues, and evaluate AI model success against business KPIs.

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

H2O.ai

H2O Gen AI Ecosystem Overview - Level 2

Dive into H2O's GenAI platform's advanced capabilities, from data preparation to model deployment, guided by Kaggle Grand Master Sanyam Bhutani through practical techniques and real-world applications.

• Coursera
• 1 hour 11 minutes
• Self-Paced
• Paid Course

SAS Certification Practice Exams

Master SAS certification readiness with three practice exams covering applied statistics, machine learning using Viya, and ModelOps for comprehensive exam preparation.

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

Pragmatic AI Labs

Production ML with Hugging Face

Master production ML deployment using the Sovereign Rust Stack with zero Python dependencies across GPU, CPU, WebAssembly, and edge targets through hands-on projects.

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

Coursera

Optimize Deep Learning Models for Peak AI

Master transfer learning, model fine-tuning, and optimization techniques to deploy efficient deep learning models in production environments with balanced accuracy and performance.

• Coursera
• 1 hour 58 minutes
• Self-Paced
• Paid Course

Coursera

Deploy & Evaluate Vision Models Effectively

Master deploying computer vision models from notebooks to production—build inference pipelines, package reproducible APIs, and evaluate performance using precision, recall, and mAP like an MLOps engineer.

• Coursera
• 1 hour 49 minutes
• Self-Paced
• Paid Course

Coursera

Optimizing AI Workflows and Deploying Edge Models

Master optimizing ML workflows with PyTorch, GPU acceleration, data pipelines, and edge deployment using TensorFlow Lite for real-world AI production environments.

• Coursera
• 7 hours 35 minutes
• Self-Paced
• Paid Course

EDUCBA

Predictive Analytics with SAS: Build & Deploy Models

Master predictive analytics using SAS Enterprise Miner through hands-on model building, data preparation, neural networks, decision trees, and deployment for business applications.

• Coursera
• 14 hours 31 minutes
• Self-Paced
• Paid Course

Edureka

Getting Started with Automated Machine Learning (AutoML)

Master automated machine learning with H2O AutoML to build, evaluate, and deploy ML models efficiently without manual trial-and-error approaches.

• Coursera
• 10 hours 35 minutes
• Self-Paced
• Paid Course

Coursera

Optimize and Deploy Edge AI Models

Master edge AI deployment by evaluating ML models with TensorFlow Lite, analyzing data slices for fairness, and optimizing quantization trade-offs for reliable real-world performance.

• Coursera
• 1 hour 27 minutes
• Self-Paced
• Paid Course

AWS Machine Learning Engineer Associate Exam Prep

Prepare for the AWS Certified Machine Learning Engineer – Associate exam by mastering ML workflows, data preparation, model deployment, SageMaker, MLOps, and GenAI services on AWS.

• Coursera
• 31 hours
• Self-Paced
• Paid Course