Model Deployment Courses and Certifications

Microcredential

AWS Machine Learning Engineer Nanodegree

41 ratings at Udacity

Equip developers with AWS SageMaker skills to build and deploy ML models in production. Learn data science, model design, and best practices for real-world applications.

• Udacity
• 4 months 2 weeks 5 days 11 hours 36 minutes
• On-Demand
• Paid Course

Machine Learning Engineer

This career track teaches you everything you need to know about machine learning engineering and MLOps.

• DataCamp
• 1 day 20 hours
• On-Demand
• Free Trial Available

End-to-End Machine Learning

Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

MLOps Fundamentals

Dive into the foundations of Machine Learning Operations (MLOps), learning the concepts of productionizing and monitoring machine learning models!

• DataCamp
• 14 hours
• On-Demand
• Free Trial Available

Introduction to MLflow

Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

LLMOps: Building Real-World Applications With Large Language Models

1 rating at Udacity

Master LLMOps principles through hands-on projects: fine-tune models, deploy production applications, implement AI safety measures, and build real-world solutions like chatbots.

• Udacity
• 11 hours
• On-Demand
• Free Online Course

Machine Learning in Production in Python

Elevate your machine learning skills to production level with this focused skill track.

• DataCamp
• 19 hours
• On-Demand
• Free Trial Available

Deploying AI into Production with FastAPI

Learn how to use FastAPI to develop APIs that support AI models, built to meet real-world demands.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Designing Forecasting Pipelines for Production

Learn how to design, automate, and monitor scalable forecasting pipelines in Python.

• DataCamp
• 4 hours
• On-Demand
• Free Trial Available

Building Generative AI Solutions on Azure with OpenAI GPT Large Language Models

Master building custom AI copilots and applications using Azure AI Studio, Prompt Flow, and OpenAI models with full lifecycle management and GenAIOps deployment strategies.

• Udacity
• 10 hours
• On-Demand
• Paid Course

Deploying a Machine Learning Model with FastAPI

Master FastAPI deployment techniques for machine learning models using real Census data, covering development, monitoring, and production launch strategies.

• Udacity
• 5 hours
• On-Demand
• Paid Course

Building a Reproducible Model Workflow

Learn to build efficient, reproducible machine learning pipelines using MLflow, pytest, and Weights & Biases. Master data validation, experiment tracking, and model deployment for real-world ML projects.

• Udacity
• 21 hours
• On-Demand
• Paid Course

Introduction to Machine Learning

Explore machine learning concepts and workflows using AWS SageMaker, from data analysis to model deployment. Learn to apply ML techniques, use advanced algorithms, and optimize models for real-world scenarios.

• Udacity
• 18 hours
• On-Demand
• Paid Course

Open Data Science

Kubeflow and Beyond - Automation of Model Training, Deployment and Testing

Automate ML workflow: data gathering, model training, deployment, testing, and production inferencing with a single command. Streamline the process for efficient continuous delivery.

• YouTube
• 50 minutes
• On-Demand
• Free Video

Databricks

Unified MLOps: Feature Stores and Model Deployment

Explore a new MLOps approach merging databases, feature stores, and ML for scalable model production. Learn about Splice Machine's hybrid database and its applications in feature engineering and model deployment.

• YouTube
• 29 minutes
• On-Demand
• Free Video