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No-Code ML with AWS SageMaker Canvas: Build AI Models Fast
Learn to create machine learning models without coding using AWS SageMaker Canvas. Master ML basics and projects.
Course Cost
₹ 2,699
Beginner
Skill Level
6 Hours
Self-paced lessons
This practical course teaches no-code machine learning using AWS SageMaker Canvas. Beginning with ML fundamentals and AWS basics, students learn to set up and navigate the SageMaker environment. Through four hands-on projects including spam detection, customer churn prediction, and wine quality analysis, learners master model building, training, and validation. The curriculum emphasizes practical application with real-world datasets, teaching essential ML concepts without requiring programming knowledge.
English
What you'll learn
Set up and navigate AWS SageMaker Canvas environment
Build and train ML models without coding
Create predictive models for real-world applications
Manage data and model versions effectively
Validate model accuracy and performance
Implement ML solutions for business problems
Skills you'll gain
This course includes:
73 Minutes PreRecorded video
5 assignments
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.
CREATED BY
PROVIDED BY
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
CREATED BY
PROVIDED BY
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.
There are 12 modules in this course
This comprehensive course introduces no-code machine learning using AWS SageMaker Canvas. Students learn essential ML concepts and AWS fundamentals before diving into practical projects. The curriculum includes setting up SageMaker domains, managing data in S3 buckets, and navigating the Canvas interface. Through four practical projects - banknote authentication, spam detection, customer churn prediction, and wine quality analysis - learners gain hands-on experience in building and validating ML models without coding.
Introduction to Machine Learning
Module 1 · 18 Minutes to complete
Introduction to AWS
Module 2 · 3 Minutes to complete
Introduction to SageMaker
Module 3 · 6 Minutes to complete
Setup
Module 4 · 21 Minutes to complete
SageMaker Canvas Interface Walkthrough
Module 5 · 2 Minutes to complete
Project 1 - Banknote Authentication
Module 6 · 21 Minutes to complete
Project 2 - Spam SMS Detection
Module 7 · 20 Minutes to complete
Project 3 - Customer Churn Prediction
Module 8 · 8 Minutes to complete
Project 4 - Wine Quality Prediction
Module 9 · 23 Minutes to complete
Assignment
Module 10 · 1 Minutes to complete
Other Important Features in SageMaker Canvas
Module 11 · 18 Minutes to complete
Congratulations and Next Steps
Module 12 · 1 Hours to complete
Fee Structure
Payment options
Financial Aid
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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.
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Frequently asked Questions
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