Duke University
MLOps | Machine Learning Operations Specialization
Duke University

MLOps | Machine Learning Operations Specialization

Become a Machine Learning Engineer. Level-up your programming skills with MLOps

Taught in English

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Noah Gift
Alfredo Deza

Instructors: Noah Gift

8,614 already enrolled

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Specialization - 4 course series

Get in-depth knowledge of a subject

3.9

(121 reviews)

Advanced level

Recommended experience

6 months at 5 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Master Python fundamentals, MLOps principles, and data management to build and deploy ML models in production environments.

  • Utilize Amazon Sagemaker / AWS, Azure, MLflow, and Hugging Face for end-to-end ML solutions, pipeline creation, and API development.

  • Fine-tune and deploy Large Language Models (LLMs) and containerized models using the ONNX format with Hugging Face.

  • Design a full MLOps pipeline with MLflow, managing projects, models, and tracking system features.

Details to know

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Specialization - 4 course series

Get in-depth knowledge of a subject

3.9

(121 reviews)

Advanced level

Recommended experience

6 months at 5 hours a week
Flexible schedule
Learn at your own pace

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  • Learn in-demand skills from university and industry experts
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  • Earn a career certificate from Duke University
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Specialization - 4 course series

Python Essentials for MLOps

Course 143 hours4.2 (118 ratings)

What you'll learn

  • Work with logic in Python, assigning variables and using different data structures.

  • Write, run and debug tests using Pytest to validate your work.

  • Interact with APIs and SDKs to build command-line tools and HTTP APIs to solve and automate Machine Learning problems.

Skills you'll gain

Category: Python Programming
Category: Information Engineering
Category: Machine Learning
Category: Test Automation
Category: MLOps

DevOps, DataOps, MLOps

Course 244 hours3.8 (49 ratings)

What you'll learn

  • Build operations pipelines using DevOps, DataOps, and MLOps

  • Explain the principles and practices of MLOps (i.e., data management, model training and development, continuous integration and delivery, etc.)

  • Build and deploy machine learning models in a production environment using MLOps tools and platforms.

Skills you'll gain

Category: Python Libraries
Category: Big Data
Category: Machine Learning
Category: Devops
Category: Rust Programming

MLOps Platforms: Amazon SageMaker and Azure ML

Course 330 hours3.8 (27 ratings)

What you'll learn

  • Apply exploratory data analysis (EDA) techniques to data science problems and datasets.

  • Build machine learning modeling solutions using both AWS and Azure technology.

  • Train and deploy machine learning solutions to a production environment using cloud technology.

Skills you'll gain

Category: Microsoft Azure
Category: Python Programming
Category: Machine Learning
Category: Amazon Web Services (Amazon AWS)
Category: MLOps

MLOps Tools: MLflow and Hugging Face

Course 425 hours3.7 (20 ratings)

What you'll learn

  • Create new MLflow projects to create and register models.

  • Use Hugging Face models and datasets to build your own APIs.

  • Package and deploy Hugging Face to the Cloud using automation.

Skills you'll gain

Category: Modeling
Category: Information Engineering
Category: Cloud Computing
Category: hugging face
Category: Machine Learning Software

Instructors

Noah Gift
Duke University
40 Courses91,762 learners

Offered by

Duke University

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