Course Outline
Pre-Requisites
We recommend that attendees of this course have working knowledge of a programming language.
Lessons
This one day course covers to solve a real-world use case with machine learning and produce actionable results using Amazon SageMaker. This course teaches you how to use Amazon SageMaker to cover the different stages of the typical data science process, from analyzing and visualizing a data set, to preparing the data and feature engineering, down to the practical aspects of model building, training, tuning and deployment.
This course includes AWS Training Exclusives.
WHAT YOU'LL LEARN
- Prepare a dataset for training.
- Train and evaluate a machine learning model.
- Automatically tune a machine learning model.
- Prepare a machine learning model for production.
- Think critically about machine learning model results.
OUTLINE
This course covers the following concepts:
- Business problem: Churn prediction
- Load and display the dataset
- Assess features and determine which Amazon SageMaker algorithm to use
- Use Amazon Sagemaker to train, evaluate, and automatically tune the model
- Deploy the model
- Assess relative cost of errors
WHO SHOULD ATTEND
A technical audience at an intermediate level
Cancellation Policy
We require 16 calendar days notice to reschedule or cancel any registration. Failure to provide the required notification will result in 100% charge of the course. If a student does not attend a scheduled course without prior notification it will result in full forfeiture of the funds and no reschedule will be allowed. Within the required notification period, only student substitutions will be permitted. Reschedules are permitted at anytime with 16 or more calendar days notice. Enrollments must be rescheduled within six months of the cancel date or funds on account will be forfeited.
Training Location
Online Classroom
your office
your city,
your province
your country
I would never take another course that starts at 11AM and goes to 9PM again. The way the course was laid out really took away from the capturing of what was presented as it was 5-6 hours of watching a screen before getting to the actual labs. There has to be a better way to lay out this particular course. In my previous course, the lectures were broken up by labs which worked out fantastic and kept you engaged in the course. There were days when in order to actually complete the labs, would go over the 9PM day end time frame. Was able to get the primary labs done, but if you want to get all the content completed, you cannot complete it in the window of this course, you will need to come back on your own time.