Learn how to apply Machine Learning Operations (MLOps) to solve real-world problems. The course covers end-to-end solutions with Artificial Intelligence (AI) pair programming using technologies like GitHub Copilot to build solutions for machine learning (ML) and AI applications. This course is for people working (or seeking to work) as data scientists, software engineers or developers, data analysts, or other roles that use ML.
DevOps, DataOps, MLOps
Give your career the gift of Coursera Plus with $160 off, billed annually. Save today.
DevOps, DataOps, MLOps
This course is part of MLOps | Machine Learning Operations Specialization
Instructors: Noah Gift
23,595 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
4.2
(120 reviews)
Advanced level
Recommended experience
Flexible schedule
Approx. 44 hours
Learn at your own pace
93%
Most learners liked this course
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
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
13 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
This course is part of the MLOps | Machine Learning Operations Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
There are 5 modules in this course
In this module, you will learn how to apply foundational skills in MLOps to build machine learning solutions and apply it by building microservices in Python.
What's included
22 videos10 readings4 assignments2 discussion prompts1 ungraded lab
In this module, you will learn how to apply essential skills in math and data science for MLOps and apply it by building simulations.
What's included
5 videos9 readings3 assignments3 ungraded labs
In this module, you will learn how to build operations pipelines and then apply these skills by building solutions for pre-trained Hugging Face models.
What's included
20 videos9 readings1 assignment2 ungraded labs
In this module, you will learn how to build end to end MLOps and AIOps solutions and apply it by building solutions with pre-trained models from OpenAI while benefiting from using AI Pair Programming tools like GitHub Copilot.
What's included
12 videos9 readings1 assignment2 ungraded labs
In this module, you will learn how to switch from Python to Rust, a powerful and efficient systems programming language. This module will cover various practical applications of Rust, such as CLI, Web, and MLOps solutions, as well as cloud computing solutions for AWS, GCP, and Azure. You'll also learn how to build Rust solutions for Kubernetes, Docker, Serverless, Data Engineering, Data Science, and Machine Learning Operations (MLOps). By the end of this module, you will have a strong understanding of Rust's key syntax and features, and be able to leverage Rust for GPU-accelerated machine learning tasks.
What's included
25 videos11 readings4 assignments3 ungraded labs
Instructors
Instructor ratings
4.3 (44 ratings)Offered by
Recommended if you're interested in Machine Learning
Duke University
Duke University
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Learner reviews
Showing 3 of 120
4.2
120 reviews
- 5 stars
56.66%
- 4 stars
20.83%
- 3 stars
10.83%
- 2 stars
5.83%
- 1 star
5.83%
New to Machine Learning? Start here.
Open new doors with Coursera Plus
Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.