Machine Learning Model Deployment Courses and Certifications

AI Workflow: Enterprise Model Deployment

62 ratings at Coursera

Explore Apache Spark, Docker, and Watson Machine Learning for enterprise model deployment. Learn best practices for data manipulation, model training, and tuning, focusing on recommender systems and scalable solutions.

• Coursera
• 9 hours 16 minutes
• Self-Paced
• Paid Course

EDUCBA

Splunk Administration and Advanced Topics

49 ratings at Coursera

Comprehensive training on Splunk administration, advanced data analysis, and security essentials. Master user management, data correlation, machine learning, and incident response for optimal Splunk deployment.

• Coursera
• 8 hours 29 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

AI Infrastructure: Deployment Types

Explore Google Cloud's AI infrastructure deployment strategies, from Compute Engine to Kubernetes, with hands-on cluster creation and inference optimization techniques.

• Coursera
• 5 hours 11 minutes
• Self-Paced
• Paid Course

AWS Certified AI Practitioner Exam Prep

Master AI, ML, and generative AI concepts on AWS while preparing for the AWS Certified AI Practitioner exam, covering responsible AI, SageMaker, and prompt engineering.

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

Deploy ML Model in Production with FastAPI and Docker

706 ratings at Udemy

Deploy ML Model with ViT, BERT and TinyBERT HuggingFace Transformers with Streamlit, FastAPI and Docker at AWS

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

Great Learning

Machine Learning Model Deployment Using Heroku - Heroku Tutorial for Beginners

Great Learning brings you this tutorial on Machine Learning Model Deployment Using Heroku to take you from the starting point through the finishing point of everything you need to know about this domain and getting started on the journey to master it.

• YouTube
• 35 minutes
• Self-Paced
• Free Video

HashiCorp

Streamline Your Machine Learning Model Deployment Lifecycle with Terraform

Master infrastructure automation for ML model deployments using Terraform Cloud and ServiceNow to accelerate delivery, ensure governance, and optimize cloud resource provisioning.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Operationalizing Machine Learning on SageMaker

2 ratings at Udacity

Learn advanced techniques for deploying professional ML projects on SageMaker, covering resource management, distributed training, high-throughput pipelines, and security in AWS.

• Udacity
• 18 hours
• Self-Paced
• Paid Course

Cloud Run for AI Inference

AI inference is the process of using a trained machine learning model to make predictions on new, unseen data by applying learned patterns. This course is designed for developers, data scientists, and ML engineers interested in quickly deploying AI infer…

• Google Skills
• 1 hour 15 minutes
• Self-Paced
• Free Online Course

Train and manage a machine learning model with Azure Machine Learning

Learn to use Azure Machine Learning for data handling, compute management, environment setup, job execution, model tracking with MLflow, and deploying models to online endpoints for real-time inferencing.

• Microsoft Learn
• 4 hours 34 minutes
• Self-Paced
• Free Online Course

Deploy and consume models with Azure Machine Learning

Learn to deploy and consume machine learning models using Azure, covering managed online endpoints for real-time inferencing and batch endpoints for large-scale processing with the Python SDK v2.

• Microsoft Learn
• 1 hour 29 minutes
• Self-Paced
• Free Online Course

Implementing Canary Releases of TensorFlow Model Deployments with Kubernetes and Anthos Service Mesh

In this lab you will install the Anthos Service Mesh, and deploy a resnet model, all on a GKE cluster.

• Google Skills
• 1-2 hours
• Self-Paced
• Paid Course

Autoscaling TensorFlow Model Deployments with TF Serving and Kubernetes

AutoML Vision helps developers with limited ML expertise train high quality image recognition models. In this hands-on lab, you will learn how to train a custom model to recognize different types of clouds (cumulus, cumulonimbus, etc.).

• Google Skills
• 1-2 hours
• Self-Paced
• Paid Course

TFX on Google Cloud Vertex Pipelines

In this lab you will develop, deploy, and run a TFX pipeline on Google Cloud Vertex Pipelines.

• Google Skills
• 1-2 hours
• Self-Paced
• Paid Course