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Introduction to SageMaker for Data Analysts

Course Summary

The Introduction to SageMaker for Data Analysts training course teaches data analysts the ability to build, train, and deploy Machine Learning (ML) models quickly. It gives analysts insight into SageMaker as a fully-managed service that covers the entire ML workflow.

The course begins with students learning the ability to label and prepare data, choosing an algorithm, and training the algorithm. Next, the course covers how to tune and optimize the algorithm for deployment, make predictions, and take action. The course concludes with a lesson on forecasting.

This course includes a hands-on investigation of datasets as well as plotting data with Amazon SageMaker. Course participants should have a familiarity with programming in at least one programming language and a basic familiarity with AWS.

Purpose
 Learn how to choose the right questions to ask and how to answer them with ML.
Audience
 Developers who need to learn SageMaker for ML.
Role
Business Analyst - Data Engineer - Data Scientist - Software Developer
Skill Level
Introduction
Style
Workshops
Duration
1 Day
Related Technologies
AWS | SageMaker

 

Productivity Objectives
  • Describe how Machine Learning differs from business analytics
  • Discern forecasting and how it is done in SageMaker
  • Apply skills learned to predictive analysis (price prediction)

What You'll Learn:

In the Introduction to SageMaker for Data Analysts training course, you'll learn:
  • What is Machine Learning and How it is Different From Business Analytics
    • Workshop: coming up with Machine Learning use cases
    • Hands-on: investigating datasets using SageMaker SQL
    • Visuals: plotting your data in SageMaker Jupyter notebooks
  • Price Prediction
    • House price prediction
    • Where price prediction is applicable
    • How it is done in SageMaker
  • Forecasting
    • Introduction to forecasting
    • Model, seasonality, other factors
    • How forecasting is done in SageMaker
real world content

Real-World Content

Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
expert practitioners

Expert Practitioners

Industry experts that bring their battle scars into the classroom.
experiential learning

Experiential Learning

More coding than lecture, coupled with architectural and design discussions.
tailored outlines

Tailored Outlines

One-size-fits-all doesn't apply to training teams. That's where we come in!
“I appreciated the instructor's technique of writing live code examples rather than using fixed slide decks to present the material.”

VMware

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