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Web & Full-Stack DevelopmentUdemy2024-12 Edition100% Free Video Course

2025 Deploy ML Model in Production with FastAPI and Docker

2025 Deploy ML Model in Production with FastAPI and Docker, the ML model deployment training course in production with FastAPI and Docker has been published by Yudemy Academy. Discover the power of seamless ML model deployment with our comprehensive course, Deploying Production-Grade ML Models with FastAPI, AWS, Docker, and NGINX. This course is designed for data scientists, machine learning engineers, and cloud professionals who are ready to take their models from development to production. You’ll gain the skills needed to deploy, scale, and manage your machine learning models in real-world environments and ensure they’re robust, scalable, and secure. In today’s fast-paced technology landscape, the ability to deploy machine learning models in manufacturing is a highly sought-after skill. This course combines the latest technologies – FastAPI, AWS, Docker, NGINX and Streamlit – into a powerful learning journey. Whether you’re looking to advance your career or upgrade your skill set, this course provides everything you need to confidently deploy, scale, and manage production-grade ML models. By the end of this course, you will have the expertise to deploy machine learning models that are not only effective, but also scalable, secure, and production-ready in real-world environments. Join us and take the next step in your machine learning journey.

146 Video Lessons
49 Hours On-Demand
Created by Udemy
Uploaded Sep 2026
English
all levels
2025 Deploy ML Model in Production with FastAPI and Docker
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Course Features:
49 hours on-demand video
146 complete lectures
Streamable on mobile, tablet & desktop
Self-paced curriculum with progress tracking
Direct MP4 downloads & offline video access
Verified course archives hosted on cloud infrastructure.

What You'll Master in this Course

Deploying Machine Learning Models with FastAPI: Learn how to build and deploy RESTful APIs to efficiently serve ML models.
Cloud-based ML deployment with AWS: Get hands-on experience deploying, managing, and scaling ML models on AWS EC2 and S3.
Automate ML operations with Boto3 and Python: Automate cloud tasks such as instance creation, data storage, and security configuration using Boto3.
Containerize ML applications using Docker: Build and manage Docker containers to ensure consistent and scalable ML deployments across environments.
Simple model inference with real-time APIs: Create high-performance APIs that deliver fast and accurate predictions for production-grade applications.
Optimizing machine learning pipelines for production: design and implement end-to-end ML pipelines, from data acquisition to model deployment, using best practices.
Implement a secure and scalable ML infrastructure: Learn to integrate security protocols and scalability features into your cloud-based ML deployment.
Build interactive web applications with Streamlit: Build and deploy ML-based interactive web applications that are accessible and user-friendly.

Course Curriculum146 Lectures

16 sections • 49 hours total length

Prefer offline learning? Download all 146 video lectures and project files for free.
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Requirements

  • Introductory knowledge of NLP
  • Comfortable in Python, Keras, and TensorFlow 2
  • Basic Elementary Mathematics

Description

2025 Deploy ML Model in Production with FastAPI and Docker, the ML model deployment training course in production with FastAPI and Docker has been published by Yudemy Academy. Discover the power of seamless ML model deployment with our comprehensive course, Deploying Production-Grade ML Models with FastAPI, AWS, Docker, and NGINX. This course is designed for data scientists, machine learning engineers, and cloud professionals who are ready to take their models from development to production. You’ll gain the skills needed to deploy, scale, and manage your machine learning models in real-world environments and ensure they’re robust, scalable, and secure. In today’s fast-paced technology landscape, the ability to deploy machine learning models in manufacturing is a highly sought-after skill. This course combines the latest technologies – FastAPI, AWS, Docker, NGINX and Streamlit – into a powerful learning journey. Whether you’re looking to advance your career or upgrade your skill set, this course provides everything you need to confidently deploy, scale, and manage production-grade ML models. By the end of this course, you will have the expertise to deploy machine learning models that are not only effective, but also scalable, secure, and production-ready in real-world environments. Join us and take the next step in your machine learning journey.

Instructor

U

Udemy

Specialist in Web & Full-Stack Development

Passionate educator focused on real-world practical skills, modern frameworks, and production-ready engineering practices. Delivering step-by-step masterclasses accessible to learners globally on MJ Accedemy.

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