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Machine Learning Operations Coursera

Highlights
Tuition fee
Free
Free
Unknown
Tuition fee
Free
Free
Unknown
Duration
6 months
Duration
6 months
Apply date
Anytime
Unknown
Apply date
Anytime
Unknown
Start date
Anytime
Unknown
Start date
Anytime
Unknown
Taught in
English
Taught in
English

About

Level-up your programming skills with MLOps. This Machine Learning Operations course course is offered by Coursera in partnership with Duke University. 

Overview

This Machine Learning Operations course course is offered by Coursera in partnership with Duke University. 

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.

Skills you'll gain

  • Microsoft Azure
  • Big Data
  • Data Analysis
  • Python Programming
  • Github
  • Machine Learning
  • Cloud Computing
  • Data Management
  • Devops
  • Amazon Web Services (Amazon AWS)
  • Rust Programming
  • MLOps

Programme Structure

Courses included:

  • Python Essentials for MLOps
  • DevOps, DataOps, MLps
  • MLOps Platforms: Amazon SageMaker and Azure ML
  • MLOps ToolsL MLflow and Hugging Face

Key information

Duration

  • Part-time
    • 6 months
    • 5 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online

Campus Location

  • Mountain View, United States

What students do after studying

Join for free or log in to access our complete career info list.

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

  • Advanced level
  • You should have basic Python programming experience, familiarity with computer science concepts, and a strong foundation in mathematics (especially linear algebra and statistics). 

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
  • International

    Non-residents
    Free
  • Out-of-State
    Free

Additional Details

  • Coursera Plus: Subscribe to build job-ready skills from world-class institutions.
  • $59/month, cancel anytime or $399/year with 14-day money-back guarantee

Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project

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