Model Deployment Courses and Certifications

DP-3007: Train and Deploy a Machine Learning Model with Azure Machine Learning (Live Online)

8 ratings at CourseHorse

Master the complete machine learning lifecycle with this hands-on course.

• CourseHorse
• 6 hours
• On-Demand
• $595.00

Coursera

Snowflake for Data Science: Intro to Snowpark ML for Python

Learn to build end-to-end machine learning workflows using Snowpark ML for Python. Master data preprocessing, model training, and deployment in Snowflake's data cloud environment.

• Coursera
• 2 hours 40 minutes
• On-Demand
• Paid Course

Pragmatic AI Labs

Large Language Models with Azure

Harness Azure's AI Power: Master Large Language Models, (LLMs) Optimize Deployments, and Build Cutting-Edge Applications.

• edX
• 4 weeks, 3-6 hours a week
• On-Demand
• Free Online Course (Audit)

Working with Notebooks in Vertex AI

Explore Vertex AI Notebooks: a unified Jupyter-based platform for machine learning workflows. Learn about notebook types, features, creation, and management in Google Cloud's ML environment.

• Coursera
• 2 hours 34 minutes
• On-Demand
• Paid Course

Introduction to Vertex Forecasting and Time Series in Practice

Learn to build forecasting solutions using Google Cloud, covering sequence models, time series analysis, and end-to-end workflows with Vertex AI. Gain practical skills through retail use cases and hands-on model development.

• Coursera
• 15 hours 7 minutes
• On-Demand
• Paid Course

Coursera

TensorFlow for Beginners: Basic Binary Image Classification

Learn to build and train a neural network for classifying cat and dog images using TensorFlow. Covers data preprocessing, CNN architecture, hyperparameter tuning, and model evaluation techniques.

• Coursera
• 3 hours 12 minutes
• On-Demand
• Paid Course

Predict Baby Weight with TensorFlow on AI Platform

In this lab you train, evaluate, and deploy a machine learning model to predict a baby’s weight. You then send requests to the model to make online predictions. This lab is part of a series of labs on processing scientific data.

• Coursera
• 1 hour 30 minutes
• On-Demand
• Paid Course

AWS Certified Machine Learning - Specialty

Master the complete machine learning lifecycle on AWS, from data engineering to model deployment, preparing you for the specialty certification exam.

• Coursera
• 7 hours 28 minutes
• On-Demand
• Paid Course

Build and Deploy an Agent with Reasoning Engine in Vertex AI

Develop and implement an AI agent with reasoning capabilities using Vertex AI SDK for Python in Google Cloud.

• Coursera
• 1 hour
• On-Demand
• Paid Course

Coursera

Advanced Data Science Techniques (with AWS Integration)

Master sophisticated ML models and AWS deployment through hands-on projects covering feature engineering, time series analysis, and cloud-based machine learning pipelines.

• Coursera
• 1 day 5 hours 29 minutes
• On-Demand
• Paid Course

Coursera

Operationalizing ML Models: MLOps for Scalable AI

Master MLOps practices to transform ML prototypes into scalable, production-ready systems using Docker, MLflow, and Kubernetes. Automate deployments, monitor performance, and optimize AI infrastructure for robust applications.

• Coursera
• 3 hours 40 minutes
• On-Demand
• Paid Course

Learn MLOps for Machine Learning

Discover how to streamline ML workflows with DVC, MLFlow, and AWS tools for tracking experiments, versioning data, and automating model deployment processes.

• Coursera
• 6 hours 39 minutes
• On-Demand
• Paid Course

Pragmatic AI Labs

MLOps Tools: MLflow and Hugging Face

Enhance your MLOps Journey: Explore MLflow and Hugging Face for Streamlined ML Lifecycle Management.

• edX
• 4 weeks, 3-6 hours a week
• On-Demand
• Free Online Course (Audit)

Coursera

Databricks Machine Learning Fundamentals

Master production-grade machine learning on Databricks with hands-on experience in data preparation, MLflow tracking, and model deployment for real-world applications.

• Coursera
• 3 hours 53 minutes
• On-Demand
• Paid Course

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
• On-Demand
• Paid Course