Machine Learning Model Deployment Courses and Certifications

Developing Machine Learning Models for Production

Shift to an MLOps mindset, enabling you to train, document, maintain, and scale your machine learning models to their fullest potential.

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

A to Z (NLP) Machine Learning Model building and Deployment.

162 ratings at Udemy

Python, Docker, Flask, GitLab, Jenkins tools and technology used for deploy model in your Local server. A complete Guide

• Udemy
• 4 hours 56 minutes
• On-Demand
• Paid Course

Nicholas Renotte

Deploying Machine Learning Models Online with Watson Machine Learning - Python Scikit-Learn

Learn to deploy Scikit-Learn models to the cloud using Watson Machine Learning, enabling online access and integration with various programming languages in under 30 minutes.

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

Prodramp

Gradio AI Web Application - Hands-On Python Example With JoJoGAN Face Stylization Model

Learn to deploy a JoJoGAN face stylization model using Gradio in Google Colab. Hands-on tutorial covers model setup, inference code, GPU-to-CPU conversion, and creating a public web application interface.

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

Machine Learning Deep Learning Model Deployment

957 ratings at Udemy

Serving TensorFlow Keras PyTorch Python Flask Serverless REST API MLOps MLflow NLP Generative AI OpenAI GPT Copilot

• Udemy
• 6 hours 34 minutes
• On-Demand
• Paid Course

Machine Learning Model Deployment with Streamlit

789 ratings at Udemy

Deploy ML models with Streamlit and share your data science work with the world

• Udemy
• 7 hours 14 minutes
• On-Demand
• Paid Course

Great Learning

Machine Learning Model Deployment Using Flask - Flask Tutorial

Learn to deploy machine learning models using Flask, covering key concepts, architecture, deployment options, and a step-by-step guide for practical implementation.

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

MLOps Deployment and Life Cycling

11 ratings at DataCamp

In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.

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

Machine Learning Model Deployment with Flask, React & NodeJS

176 ratings at Udemy

Use web development tools Node.JS, React and Flask to deploy your Data Science models to web apps!

• Udemy
• 3 hours 57 minutes
• On-Demand
• Paid Course

Deployment of Machine Learning Models

5888 ratings at Udemy

Learn how to integrate robust and reliable Machine Learning Pipelines in Production

• Udemy
• 10 hours 27 minutes
• On-Demand
• Paid Course

Microcredential

TensorFlow: Data and Deployment

1475 ratings at Coursera

Explore advanced TensorFlow deployment scenarios across browsers, mobile devices, and various platforms. Learn data pipeline management, model retraining, and privacy-preserving techniques for real-world AI applications.

• Coursera
• 4 weeks, 10 hours a week
• On-Demand
• Paid Course
• 4 courses

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
• On-Demand
• Paid Course

Device-based Models with TensorFlow Lite

655 ratings at Coursera

Learn to deploy machine learning models on mobile and embedded devices using TensorFlow Lite. Optimize for low-power environments and run models on Android, iOS, Raspberry Pi, and microcontrollers.

• Coursera
• 10 hours 19 minutes
• On-Demand
• Paid Course

Data Pipelines with TensorFlow Data Services

536 ratings at Coursera

Streamline ETL tasks, optimize data pipelines, and publish datasets using TensorFlow Data Services. Learn to load, process, and share standardized data efficiently for machine learning models.

• Coursera
• 11 hours 13 minutes
• On-Demand
• Paid Course

Advanced Deployment Scenarios with TensorFlow

512 ratings at Coursera

Explore advanced deployment scenarios using TensorFlow Serving, TensorFlow Hub, TensorBoard, and federated learning to effectively bring machine learning models into real-world applications.

• Coursera
• 12 hours 52 minutes
• On-Demand
• Paid Course