Free Amazon SageMaker Course
Amazon Sagemaker Course
4.5
Beginner level
3.75 learning hrs
Learners can use this Amazon SageMaker course for free to understand AWS machine learning workflows, SageMaker architecture, demos, and AI services used in cloud ML projects.
Instructor:
Mr. Vishal Padghan
About this course
Cloud machine learning becomes easier to evaluate when learners know where SageMaker fits in AWS. This Amazon SageMaker course for free introduces AWS for AI, the machine learning product stack, SageMaker architecture, a SageMaker demo, and services such as Comprehend, Polly, Textract, Transcribe, Forecast, and Personalize. These details support searches for Amazon SageMaker course, AWS SageMaker course, and machine learning with AWS.
The course is useful for learners exploring cloud ML tools before deeper AWS certification or ML engineering. It shows how SageMaker relates to adjacent AWS AI services for text, speech, document extraction, forecasting, and personalization use cases. Learners can understand architecture, service selection, and the foundation needed to discuss or explore cloud-based AI workflows with more confidence.
Course outline
Machine Learning with AWS
This module briefs the Amazon Sagemaker, Amazon Comprehend, Amazon Lex, Amazon Polly, Amazon Recognition, Amazon Deeplens, and Amazon Textract components of AWS.
Why AWS for AI?
AI can be created in a proprietary manner, and it's also not a necessity for a business solution. So why exactly should we use the AI services provided in AWS? Let's answer this question in this module.
Machine Learning Stack of Products
AI and ML are two sides of the same coin and go hand in hand. So, let's look into some of the service domains provided in AWS for AI and ML services.
Amazon SageMaker
In the first module, you will understand the basics of a machine learning model that a Data Scientist prepares for data processing. You will also understand what AWS Sagemaker is and how it is used.
Amazon SageMaker Architecture
This module discusses the Architecture of the AWS Sagemaker and its applications. Later on, you will understand the data processing procedure.
Amazon SageMaker Demo
In the last module, you will understand the dashboard of an AWS Sagemaker. Later on, the course demonstrates a sample program. You will learn about the steps for creating a data manipulation machine learning model by creating Jupyter notebook instances, uploading the datasets, and training the data model with the help of Machine Learning algorithms.
Amazon Comprehend and Amazon Polly
Amazon Comprehend is an AWS service that develops insights by recognizing the common elements. Amazon Polly, on the other hand, is a Text-To-Speech synthesizer. Let's look into some of the most pertinent features of these services.
Amazon Textract and Amazon Transcribe
Amazon Textract is a text detection and analysis AI service provided by AWS. Amazon Transcribe is a speech recognizer and analyzer service provided by AWS. Let's look into some of the most pertinent features of these services.
Amazon Forecast and Amazon Personalize
Amazon Forecast delivers highly accurate time-series forecasts based on statistical and machine learning algorithms as an AWS service. Amazon Personalize is an AI-based AWS service that aids businesses in delivering personalized experiences to their users. Let's look into some of the most pertinent features of the both these services.
Get access to the complete curriculum once you enroll in the course
4.5
What our learners enjoyed the most
Skill & tools
65% of learners found all the desired skills & tools
Our course instructor
Mr. Vishal Padghan
Cloud Computing Expert
Frequently Asked Questions
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