Unlocking MLOps: Build, Deploy, and Automate Your ML Models

Dive into the transformative world of MLOps with our hands-on bootcamp designed to seamlessly transition DevOps and infrastructure engineers into this thriving field. In this course, you’ll experience the integration of machine learning models with real-world applications, making you a key player in modern software development.

Starting with the basics, you’ll learn to set up your environment using Docker and MLflow, followed by practical exercises in data processing, feature engineering, and experiments using Jupyter notebooks. As you progress, you’ll package models using FastAPI and deploy them alongside a Streamlit-based UI, mastering continuous integration pipelines with GitHub Actions.

The latter part of the course focuses on building scalable inference infrastructure using Kubernetes, incorporating monitoring practices with Prometheus and Grafana, and utilizing Seldon Core for production-grade model delivery. By the end of this course, you’ll be equipped with the necessary skills to automate machine learning workflows, paving the way for a successful career as an MLOps and AI platform engineer.

What you will learn:

• Building, tracking, and deploying ML models using MLflow, Docker, and Kubernetes
• Developing practical ML applications with Streamlit and FastAPI
• Automating CI/CD pipelines with GitHub Actions
• Constructing scalable inference infrastructure on Kubernetes
• Delivering production-ready models with Seldon Core and monitoring with Prometheus/Grafana
• Managing continuous delivery in a GitOps style using ArgoCD

Course Content:

• Sections: 6
• Lectures: 58
• Duration: 8h 43m

Requirements:

• Basic knowledge of Python (functions, data structures, etc.)
• Understanding of basic Docker and Git operations
• Familiarity with Linux command line
• Basic understanding of machine learning (scikit-learn and regression fundamentals) desired
• Knowledge of Kubernetes is beneficial but the course covers necessary content

Who is it for?

• DevOps engineers and infrastructure engineers looking to expand into AI/ML
• Data scientists and ML engineers wanting to gain practical MLOps skills
• Individuals interested in deploying their ML projects to production environments
• Those aiming to develop, build, and operate ML applications applicable in real-world scenarios
• Aspiring AI platform engineers

What are you waiting for to get started?

Enroll today and take your skills to the next level. Coupons are limited and may expire at any time!

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