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
• Self-Paced
• Free Trial Available

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
• Self-Paced
• 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
• Self-Paced
• Free Video

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
• Self-Paced
• 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
• Self-Paced
• Free Trial Available

MLOps for Business

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

• DataCamp
• 3 hours
• Self-Paced
• Free Trial Available

Machine Learning Deep Learning Model Deployment

1005 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
• Self-Paced
• Paid Course

Machine Learning Model Deployment with Streamlit

809 ratings at Udemy

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

• Udemy
• 7 hours 14 minutes
• Self-Paced
• Paid Course

Credential

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/week
• Self-Paced
• Paid Course
• 4 courses

Edge Impulse Credential

Edge AI for Microcontrollers

889 ratings at Coursera

Discover how to build and deploy AI models on microcontrollers, covering fundamentals, sensor data processing, and computer vision for resource-constrained devices.

• Coursera
• 8 weeks, 4 hours/week
• Self-Paced
• Paid Course
• 3 courses

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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• 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
• Self-Paced
• Paid Course

Credential

Python Data Products for Predictive Analytics

299 ratings at Coursera

Master Python for predictive analytics: Create data strategies, develop statistical models, and deploy machine learning models to make accurate predictions for business and research purposes.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 4 courses