Model Deployment Courses and Certifications

tinyML

TinyML Talks - Speech-to-Intent Model Deployment to Low-Power Low-Footprint Devices

Explore techniques for training and deploying speech-to-intent models on low-power microcontrollers, enabling efficient voice control in resource-constrained devices.

• YouTube
• 1 hour
• Self-Paced
• Free Video

Prodramp

One-Shot Face Stylization with JoJoGAN - Model Save, Export and Deployment

Learn to save, export, and deploy JoJoGAN face stylization models. Covers checkpoint saving, model exporting, inference setup, and style application in Colab environment.

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

MLOps.community

Streamlining Model Deployment - AI in Production

Explore strategies for optimizing AI model deployment pipelines, including open governance, runtime benchmarks, and dynamic routing. Learn to make AI deployments faster, cheaper, and more accurate in a rapidly evolving landscape.

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

An Accelerated Introduction to AI Model Deployment with Cloud Native

Discover how to effectively deploy AI models in cloud environments, exploring training methods, performance optimization, and infrastructure choices for both CPU and GPU implementations.

• YouTube
• 1 hour 14 minutes
• Self-Paced
• Free Video

SNIAVideo

AI Model Inferencing and Deployment Options

Explore AI model inferencing processes and deployment strategies, covering hardware considerations, software options, and best practices for production environments.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video

Credential

Deploying ML Models in Production

Master building scalable ML systems with reusable pipelines, FastAPI web services, and automated retraining using Apache Airflow for production deployment.

• CodeSignal
• 7 hours
• Self-Paced
• Free Certificate
• 3 courses

Pragmatic AI Labs

Open Source LLMOps

Unlock Open Source AI: Dive into LLM Architectures, Fine-Tuning, and Cutting-Edge Deployments.

• edX
• 4 weeks, 3-6 hours/week
• Self-Paced
• Free Online Course (Audit)

Coursera

Deploying Open Models

Master containerization, cloud deployment, and monitoring strategies for generative AI models in production environments with hands-on Docker, AWS/GCP/Azure experience.

• Coursera
• 5 hours 23 minutes
• Self-Paced
• Paid Course

Packt

Data Science Model Deployments and Cloud Computing on GCP

Master GCP deployment of data science models using Cloud Run, App Engine, and Vertex AI with hands-on Docker containerization and serverless computing techniques.

• Coursera
• 10 hours 34 minutes
• Self-Paced
• Paid Course

Krish Naik

Deployment of ML Models - Complete Tutorial Series

Master ML model deployment across cloud platforms including Heroku, AWS, Azure, and GCP using Flask, FastAPI, and Streamlit for production-ready applications.

• YouTube
• 2 hours 56 minutes
• Self-Paced
• Free Video

Deploy a LLM Application to Vercel, Google Cloud & Azure

495 ratings at Udemy

Hands-on guide to building a Python-based Generative AI LLM app and deploying it on Vercel, Google Cloud Run, and Azure

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

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

Whizlabs

AWS: Model Training , Optimization & Deployment

Master AWS machine learning workflows through SageMaker algorithms, hyperparameter tuning, and scalable deployment strategies for the MLA-C01 certification exam.

• Coursera
• 8 hours 37 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

Introducing MLOps: From Model Development to Deployment (AI)

478 ratings at Udemy

A Practical Guide to Building, Automating, and Scaling Machine Learning Pipelines with Modern Tools and Best Practices

• Udemy
• 1 hour 49 minutes
• Self-Paced
• Paid Course