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MLOps Platforms: Amazon SageMaker and Azure ML
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MLOps Platforms: Amazon SageMaker and Azure ML

Master machine learning operations using AWS SageMaker and Azure ML for building, training, and deploying ML solutions in production.

Course Cost

Free course

Advanced

Skill Level

30 Hours

Self-paced lessons

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full MLOps Machine Learning Operations Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

3.7

5,959 Enrolled

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3.7

5,959 Enrolled

English

What you'll learn

  • Apply EDA techniques to data science problems

  • Build ML solutions using AWS and Azure platforms

  • Deploy ML models to production environments

  • Implement data engineering pipelines

  • Optimize ML workflows for cloud deployment

Skills you'll gain

AWS SageMaker
Azure ML
MLOps
Machine Learning
Cloud Computing
Data Engineering
Model Deployment
Python Programming
DevOps
Production ML

This course includes:

3.6 Hours PreRecorded video

17 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

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Certificate
Certificate

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

CREATED BY

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PROVIDED BY

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Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

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There are 5 modules in this course

This comprehensive course focuses on implementing machine learning operations (MLOps) using AWS SageMaker and Azure ML platforms. Students learn to build data engineering pipelines, perform exploratory data analysis, and develop machine learning models in cloud environments. The curriculum covers essential MLOps concepts including model training, deployment, monitoring, and maintenance in production settings. Through hands-on exercises, learners gain practical experience with both AWS and Azure technologies while preparing for cloud platform certifications.

Data Engineering with AWS Technology

Module 1 · 7 Hours to complete

Exploratory Data Analysis with AWS Technology

Module 2 · 7 Hours to complete

Modeling with AWS Technology

Module 3 · 7 Hours to complete

MLOps with AWS Technology

Module 4 · 5 Hours to complete

Machine Learning Certifications

Module 5 · 4 Hours to complete

Fee Structure

Reviews

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

MLOps Platforms: Amazon SageMaker and Azure ML

Advanced

Skill Level

30 Hours

Self-paced lessons

Course Cost

Free course

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.