Model Deployment Courses and Certifications

Board Infinity

Real-World Applications & Model Deployment in Java

Deploy machine learning models in Java: expose them through Spring Boot REST APIs, automate pipelines with Jenkins and GitHub Actions, and apply reinforcement learning and responsible AI.

• Coursera
• 3 weeks, 3 hours a week
• Self-Paced
• Paid Course

Edureka

Model Deployment and Monitoring

Operate enterprise ML systems in production: scale feature stores and distributed training with Amazon SageMaker, run governance and bias checks, and monitor drift, cost, and SLOs.

• Coursera
• 4 weeks, 2 hours a week
• Self-Paced
• Paid Course

Machine Learning in Production

3369 ratings at Coursera

Design a production ML system end to end: scope projects, deploy models against changing data, run error analysis, handle class imbalance, and set performance baselines.

• Coursera
• 3 weeks, 4 hours a week
• Self-Paced
• Paid Course

Career Certificate

TensorFlow: Data and Deployment

1475 ratings at Coursera

Deploy models to browsers and mobile devices with TensorFlow.js and TensorFlow Lite, build data pipelines with TensorFlow Data Services, and serve models using TensorFlow Serving.

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

Amazon Web Services;  Amazon

AWS ML Engineer Associate 3.1 Select a Deployment Infrastructure (Japanese)

ML パイプラインの本番推論インフラストラクチャを設計し、AWS で最適なデプロイ戦略を選択するコース。

• AWS Skill Builder
• 1 hour
• Self-Paced
• Paid Course

Amazon Web Services;  Amazon

AWS ML Engineer Associate 3.1 Select a Deployment Infrastructure (Japanese) 日本語吹き替え版

AWS上で機械学習モデルを本番環境へデプロイするための推論インフラ、デプロイ戦略、コンピューティング環境を学ぶ。

• AWS Skill Builder
• 1 hour
• Self-Paced
• Paid Course

Amazon Web Services;  Amazon

AWS ML Engineer Associate 3.1 Select a Deployment Infrastructure (日本語吹き替え版)

機械学習モデルを本番環境へデプロイするため、推論ターゲット、コンテナ、AWSコンピューティング環境を選択する方法を学びます。

• AWS Skill Builder
• 1 hour
• Self-Paced
• Paid Course

Coursera

Machine Learning Pipelines with Azure ML Studio

835 ratings at Coursera

Build an end-to-end machine learning pipeline in Azure ML Studio without code: train a Two-Class Boosted Decision Tree on census income data, evaluate it, and deploy a prediction web service.

• Coursera
• 1 hour 48 minutes
• Self-Paced
• Paid Course

Device-based Models with TensorFlow Lite

655 ratings at Coursera

Convert and optimize TensorFlow models to TensorFlow Lite, then run them with the Lite Interpreter in Android and iOS apps, on Raspberry Pi and microcontrollers.

• Coursera
• 4 weeks, 3 hours a week
• Self-Paced
• Paid Course

Deploying Machine Learning Models

54 ratings at Coursera

Build a similarity-based recommender system using gradient descent and Jaccard similarity, then deploy and monitor it with Python web server frameworks on large-scale datasets.

• Coursera
• 5 weeks, 2 hours a week
• Self-Paced
• Paid Course

Advanced Model-Driven Apps with Power Apps: Configuration, Customization, and Deployment Techniques

Advanced configuration, customization, analytics, and deployment techniques for Microsoft Power Apps model-driven apps.

• Microsoft Learn
• 3 hours 55 minutes
• Self-Paced
• Free Online Course

PyTorch for Deep Learning Bootcamp

6343 ratings at Udemy

Learn PyTorch. Become a Deep Learning Engineer. Get Hired.

• Udemy
• 2 days 4 hours 13 minutes
• Self-Paced
• Paid Course

Career Certificate

IBM AI Enterprise Workflow

387 ratings at Coursera

Build end-to-end enterprise AI solutions: ingest data, test hypotheses, engineer features, detect bias, and deploy machine learning models on IBM Cloud with Watson tooling.

• Coursera
• 8 weeks, 10 hours a week
• Self-Paced
• Paid Course
• 6 courses

AWS Machine Learning with SageMaker: Hands-On

4275 ratings at Udemy

Experience AWS SageMaker: A Practical Course with Hands-On Learning, Practice Tests. Deploy DeepSeek LLM & Hugging Face

• Udemy
• 19 hours 52 minutes
• Self-Paced
• Paid Course

Foundations of AI and Machine Learning

288 ratings at Coursera

Explore AI/ML infrastructure: build data pipelines, evaluate model frameworks and pretrained LLMs, and prepare models for production deployment with version control and scalable platforms.

• Coursera
• 5 weeks, 7 hours a week
• Self-Paced
• Paid Course