Amazon SageMaker: Simplifying Machine Learning Application Development by Amazon Web Services via Edx: Fee, Duration, How to Apply

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study	Mode of Delivery Video and Text Based	Learning efforts 2-4 Hours Per Week

Course overview

Amazon Web Services (AWS) is offering the Amazon SageMaker: Simplifying Machine Learning Application Development certification course. It will act as your guide for using Amazon SageMaker for the integration of ML or machine learning into your apps. Machine learning has surfaced as one of the most sought-after technological domains in recent times. Thus, the course can help you develop your skill-set in just a span of 4 weeks.

The Amazon SageMaker online course by edX will empower you with the knowledge of training a model with the help of a Jupyter Notebook. You will learn under the able guidance of AWS Training and Certification expert educators. Furthermore, you will have the assistance of video lectures, hands-on exercises, and demos to help you achieve fluency in the course concepts.

Moreover, the Amazon SageMaker training will allow you to hone your prior skills and help you gain new ones. You will have improved career opportunities at hand after completing this course. Although it is free of charge programme, you need to purchase the Verified Certificate track to access graded assessments and the programme certificate.

Course and certificate fees

Type of course

Free

The Amazon SageMaker: Simplifying Machine Learning Application Development certification fee is not chargeable if you do not need a certificate. you need to pay no charges. You can access and learn from the course material such as video lectures absolutely free-of-cost. But you cannot obtain the programme certificate in this way. You must pay Rs. 8,242 as the certification fee to get the course completion certificate.

Amazon SageMaker: Simplifying Machine Learning Application Development fee structure

Course	Fee in INR
Amazon SageMaker: Simplifying Machine Learning Application Development (Audit only)	Free
Amazon SageMaker: Simplifying Machine Learning Application Development course (With certificate)	Rs. 8,260

certificate availability

Yes

certificate providing authority

Amazon Web Services

certificate fees

₹8,260

Who it is for

This ML application development course will be helping those participants who would like to pursue their careers as ML Engineers by learning concepts in ML application development.

Eligibility criteria

To enrol in the Amazon SageMaker: Simplifying Machine Learning Application Development online course, you must hold work experience of application development. The course assumes some knowledge of the AWS Console. It will also be beneficial for you to pursue the AWS Developer Professional Series MOOC on edX. However, it is not compulsory.

Moreover, to receive the Amazon SageMaker: Simplifying Machine Learning Application Development certification by edX certificate, you must appear for the course-end exam and score a minimum of 65 percent marks. It is only available for candidates enrolled in the Verified Certificate track.

What you will learn

Machine learning Knowledge of amazon web services

edX's Amazon SageMaker: Simplifying Machine Learning Application Development certification syllabus helps you acquire these concepts:

Critical problems that machine learning can challenge and solve
Using the built-in algorithms of Amazon SageMaker to train a model
Using a Jupyter Notebook instance
Publishing a model with Amazon SageMaker
Integrating the published Amazon SageMaker endpoint with an app

The syllabus

Programme Introduction

Welcome
Student Information
Introduce Yourself
Meet the Instructors

Week 1

Introduction to Machine Learning with SageMaker on AWS

Introduction
Use of ML
Amazon SageMaker
Diving Right In

Weekly Quiz, Resources, Readings, Discussion

Week 1 Discussion
Week 1 Resources and Notes
Week 1 Quiz

Week 2

Amazon SageMaker SDK and Notebooks

Introduction to Week 2

Amazon SageMaker Notebooks

Jupyter Notebooks Introduction
Clean and Prepare Data: Notebooks and Libraries
Exercise 2.1: Creating a Notebook Instance
Exercise 2.1 Walkthrough

Readings, Weekly Quiz, Discussion, Resources

Week 2 Discussion
Week 2 Quiz
Week 2 Resources and Notes

Week 3

Amazon SageMaker Algorithms

Introduction to Week 3

Amazon SageMaker Terminology and ML

Hyperparameter Tuning
SageMaker/ML Terminology and Algorithms

Amazon SageMaker Algorithms

k-means Algorithm Walkthrough
Introduction to Exercise 3.1
Exercise 3.1: Using the k-means Algorithm (Optional)
XGBoost Algorithm Walkthrough (Part 1)
XGBoost Algorithm Walkthrough (Part 2)
XGBoost Algorithm Walkthrough (Part 3)
Introduction to Exercise 3.2
Exercise 3.2: Using the XGBoost Algorithm (Optional)

Weekly Quiz, Readings, Resources, Discussion

Week 3 Quiz
Week 3 Discussion
Week 3 Resources and Notes

Week 4

Application Integration

Introduction to Week 4

Integrate Amazon SageMaker with your Apps

Serverless Recap
Exercise 4.1 Walkthrough
Exercise 4.1: Python Movie Recommender (Optional)
Bring Your Own Models
Bringing Your Own Models: MXNet and TensorFlow

Weekly Quiz, Readings, Resources, Discussion

Week 4 Quiz
Week 4 Resources and Notes
Course Survey
Week 4 Discussion
Class Wrap Up

Course-end Assessment (for verified certificate track)

Admission details

Visit Amazon SageMaker: Simplifying Machine Learning Application Development claases by clicking on https://www.edx.org/learn/machine-learning/amazon-web-services-amazon-sagemaker-simplifying-machine-learning-application-development
Now, you can read the certification offerings on the programme homepage. Here, you must select “Enroll” after reading the details.
Once you tap on it, you will reach the registration page. Now, register using your email ID or Microsoft or Facebook account details to proceed.

Filling the form

The Amazon SageMaker: Simplifying Machine Learning Application Development course by edX is accessible by simply registering on edX. Interested participants need not fill out a dedicated application form.

How it helps

The Amazon SageMaker: Simplifying Machine Learning Application Development training will help you enhance your employability quotient. You will have a higher grasp of machine learning concepts, and thus, you will have greater job opportunities. Besides, by adding the course certificate to your LinkedIn profile or resume, you can stand apart from the other non-certified competitors. Thus Amazon SageMaker: Simplifying Machine Learning Application Development certification benefits are many.

Instructors

Mr Russell Sayers
Senior Cloud Technologist
Amazon Web Services

Mr Asim Jalis
Senior Technical Trainer
Amazon Web Services

Mr Carl Leonard
Technical Trainer
Amazon Web Services

FAQs

Can I enroll without prior app development experience?

To enroll in the Amazon SageMaker: Simplifying Machine Learning Application Development training, candidates must hold experience in application development. Also, a fundamental understanding of AWS services will be helpful.

What is the grading pattern of this edX Amazon SageMaker: Simplifying Machine Learning Application Development online course?

Weekly quizzes are not graded and allow unlimited retries. However, only students who have purchased the Verified Certificate track can access the course certificate and course-end examination. You need to score at least 65 per cent marks to qualify.

Will I get a certificate for this training programme?

You can earn a certificate for the programme by appearing in the course-end assessment and paying a certificate fee.

Am I eligible for transferring the earned university credits?

edX and Amazon Web Services do not provide the Amazon SageMaker certification programme participants with any university credits.

Does the Amazon SageMaker: Simplifying Machine Learning Application Development course have any associated charges?

edX offers this programme for free. However, the AWS Free Tier comes with a certain limitation of its free resources. So, if need be, you can access the graded assessments and the entire course content by taking the Verified Certificate track.