Model Deployment Courses and Certifications

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

Pragmatic AI Labs Credential

Next-Gen AI Development with Hugging Face

Master building, deploying, and scaling AI applications using Hugging Face's ecosystem through hands-on projects that run locally without cloud costs.

• Coursera
• 12 weeks, 5 hours/week
• Self-Paced
• Paid Course
• 4 courses

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
• Self-Paced
• Paid Course

Pragmatic AI Labs

Hugging Face Hub and Ecosystem Fundamentals

Discover how to navigate the Hugging Face ecosystem to find, evaluate, and deploy pre-trained ML models for text, image, and audio tasks across 500,000+ options without training from scratch.

• Coursera
• 2 hours 13 minutes
• Self-Paced
• Paid Course

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
• Self-Paced
• Paid Course

Packt

AI Agents and MLOps for Production-Ready AI

Master AI agents and MLOps to build production-ready systems using AutoGen, CrewAI, Docker, and Kubernetes for scalable deployment and automation workflows.

• Coursera
• 5 hours 28 minutes
• Self-Paced
• 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/week
• Self-Paced
• Free Online Course (Audit)

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
• Self-Paced
• Paid Course

Whizlabs

Azure ML: Deploying, Managing, and Experimenting with Models

Master Azure ML model deployment, management, and experimentation with MLOps best practices, AutoML, and Responsible AI implementation for scalable machine learning workflows.

• Coursera
• 7 hours 44 minutes
• Self-Paced
• Paid Course

Edureka

Fine-Tuning & Optimizing Large Language Models

Master parameter-efficient fine-tuning, context engineering, and deployment strategies for large language models using modern tools like Hugging Face and LoRA adapters.

• Coursera
• 13 hours 45 minutes
• Self-Paced
• Paid Course