Topics

Duration

32 Weeks

Progress

0/20

Learning Progress0%

AI Roadmap

AI Deployment & MLOps

Learning Path

Follow these concepts in order to master this topic.

Introduction to MLOps

ML Lifecycle

Model Serialization

Serving Machine Learning Models

Building APIs with FastAPI

Building APIs with Flask

Docker Fundamentals

Containerizing ML Applications

Docker Compose

Kubernetes Basics

Model Versioning

Data Versioning (DVC)

Experiment Tracking (MLflow)

Weights & Biases

CI/CD for Machine Learning

Model Monitoring

Data Drift

Model Drift

ONNX

TensorFlow Serving

TorchServe

Deploying LLM Applications

Cloud Deployment (AWS, Azure, GCP)

Building Production AI Systems

Documentation

Official documentation and references.

MLflow Documentation

Recommended

FastAPI Documentation

Docker Documentation

Kubernetes Documentation

Video Courses

MLOps Full Course

26m

Deploy Machine Learning Models with FastAPI

19m

Practice Websites

Practice what you've learned.

Hugging Face Spaces

Render

Google Colab

Projects

Apply what you've learned by building real projects.

Deploy a Machine Learning Model with FastAPI

Beginner

Deploy an Image Classification API using Docker

Intermediate

Build and Deploy a Production-Ready RAG AI Assistant

Advanced