Workshop: Machine Learning with Amazon SageMaker

Building, training and deploying machine learning models efficiently and at scale

26 July 2018, 10:00AM to 01:30PM, Auditorium 3, NIMHANS, Bangalore

Want to build ML systems quickly? Attend this workshop and learn how to build, train and deploy machine learning models efficiently and at scale.

Topics Covered:

  • What Amazon SageMaker is
  • How to build end-to-end machine learning workflows on Amazon SageMaker
  • How to use built-in ML algorithms.
  • How to bring your own model

And more..

Why Amazon SageMaker?

It removes all the barriers that typically slow down developers who want to use machine learning.

Who should attend?

Engineers, Architects and Data Scientists who are considering moving to SageMaker or integrating SageMaker to their existing ML workflow.

Note: This is a free workshop sponsored by AWS and they will be collecting participants data for generating coupons. These credits are exclusively for hands-on labs. We will be emailing links to RSVP link to The Fifth Elephant 2018 attendees. We only have limited seats and seats will be offered on a first come first serve basis.


  1. Overview of AI/ML/DL [30 mins]
  2. Amazon SageMaker overview – an overview of the SageMaker service, best use cases, main features including AWS security concepts of IAM, VPC, KMS. [ 45 mins.]
  3. Accessing SageMaker – demo to show how to easily access SageMaker service [Duration: 15 mins.]
  4. Notebook demo on using highly -optimized built-in Amazon algorithms [Duration: 30 mins.]
  5. Hands-on lab – Managed Training, Hosting and A/B Testing of Amazon built-in algorithm – Amazon linear learner algorithm / parallel training using SageMaker Estimators / SageMaker Python SDK [Duration: 60 mins.]


  • Participants should carry own laptop.
  • To participate in hands-on sessions, you need to have an AWS account. If you don’t have, please create one. You will be required to share credit card details to validate your identity. Please do create an account now as it take sometimes few hours to validate. We will be giving every participant 100$ credit for this workshop. At the end of the workshop, you should terminate all Sagemaker resources created for the workshop (notebook instance, inference endpoints etc.) and delete all workshop related data from S3 to avoid unnecessary AWS Billing.
  • There is a hands-on session and to follow this session, **participants should have an AWS Account with admin privileges in IAM.
  • All participants will be provided $100 AWS Credits for the workshop.
  • Participants should be familiar with AI / ML / DL concepts


Praveen Jayakumar

Solutions Architect





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