Trending Courses

Vendors

Skip Navigation Links

Overview

You will learn how to solve a real-world use case with Machine Learning (ML) and produce actionable results using Amazon SageMaker. This course walks through the stages of a typical data science process for Machine Learning from analyzing and visualizing a dataset to preparing the data, and feature engineering. Individuals will also learn practical aspects of model building, training, tuning, and deployment with Amazon SageMaker. Real life use case includes customer retention analysis to inform customer loyalty programs.
img-course-overview.jpg

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

Who Should Attend

This course is intended for:

  • Developers
  • Data Scientists
img-who-should-learn.png

Prerequisites

We recommend that attendees of this course have:

  • Familiarity with Python programming language
  • Basic understanding of Machine Learning

Learning Journey

Coming Soon...

Module 1: Introduction to machine learning

  • Types of ML
  • Job Roles in ML
  • Steps in the ML pipeline

Module 2: Introduction to data prep and Sage Maker

  • Training and test dataset defined
  • Introduction to Sage Maker
  • Demonstration: Sage Maker console
  • Demonstration: Launching a Jupiter notebook

Module 3: Problem formulation and dataset preparation

  • Business challenge: Customer churn
  • Review the customer churn dataset

Module 4: Data analysis and visualization

  • Demonstration: Loading and visualizing your dataset
  • Exercise 1: Relating features to target variables
  • Exercise 2: Relationships between attributes
  • Demonstration: Cleaning the data

Module 5: Training and evaluating a model

  • Types of algorithms
  • XGBoost and Sage Maker
  • Demonstration: Training the data
  • Exercise 3: Finishing the estimator definition
  • Exercise 4: Setting hyperparameters
  • Exercise 5: Deploying the model
  • Demonstration: hyperparameter tuning with Sage Maker
  • Demonstration: Evaluating model performance

Module 6: Automatically tune a model

  • Automatic hyperparameter tuning with Sage Maker
  • Exercises 6-9: Tuning jobs

Module 7: Deployment/production readiness

  • Deploying a model to an endpoint
  • A/B deployment for testing
  • Auto Scaling
  • Demonstration: Configure and test auto scaling
  • Demonstration: Check hyper parameter tuning job
  • Demonstration: AWS Auto Scaling
  • Exercise 10-11: Set up AWS Auto Scaling

Module 8: Relative cost of errors

  • Cost of various error types
  • Demo: Binary classification cutoff

Module 9: Amazon Sage Maker architecture and features

  • Accessing Amazon Sage Maker notebooks in a VPC
  • Amazon Sage Maker batch transforms
  • Amazon Sage Maker Ground Truth
  • Amazon Sage Maker Neo
        -

Frequently Asked Questions (FAQs)

  • Why get AWS certified?

    AWS certifications validate your expertise in cloud computing and your proficiency in using AWS services.

    These certifications are globally recognized and highly sought after by employers, as they demonstrate your ability to design, deploy, and manage scalable and secure cloud solutions on the AWS platform.

    AWS-certified professionals are in high demand, opening doors to new career opportunities and higher earning potential.

  • What to expect for the examination?

    AWS offers a variety of certification exams at different levels (Foundational, Associate, Professional, and Specialty) covering various domains and services.

    The exams typically consist of multiple-choice and multiple-response questions, and some may include scenario-based questions that assess your ability to apply your knowledge in real-world situations.

    Note: Certification requirements and policies may be updated by AWS from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • How long is AWS certification valid for?

    AWS certifications are valid for three years from the date of passing the exam.

    To maintain your certification, you will need to recertify by passing the latest version of the exam or completing the AWS Cloud Quest game-based training (if option is applicable).

    Note: Certification requirements and policies may be updated by AWS from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • Why take this course with Trainocate?

    Here’s what sets us apart:

    - Global Reach, Localized Accessibility: Benefit from our geographically diverse training hubs in 16 countries (and counting!).

    - Top-Rated Instructors: Our team of subject matter experts (with high average CSAT and MTM scores) are passionate to help you accelerate your digital transformation.

    - Customized Training Solutions: Choose from on-site, virtual classrooms, or self-paced learning to fit your organization and individual needs.

    - Experiential Learning: Dive into interactive training with our curated lesson plans. Participate in hands-on labs, solve real-world challenges, and take on comprehensive assessments.

    - Learn From The Best: With 30+ authorized training partnerships and countless awards from Microsoft, AWS, Google – you're guaranteed learning from the industry's elite.

    - Your Bridge To Success: We provide up-to-date course materials, helpful exam guides, and dedicated support to validate your expertise and elevate your career.

Keep Exploring

Course Curriculum

Training Schedule

Exam & Certification

Frequently Asked Questions

img-improve-career.jpg

Improve yourself and your career by taking this course.

More Courses By AWS

Browse All Courses
aws-mga-migrating-to-aws-training
Migration and Transfer

Migrating to AWS

This course is for individuals who seek an understanding of how to plan and migrate existing workloads to the AWS Cloud.
ILT VILT
Course Duration 3 Days
Fees $550.00
aws-devops-devops-engineering-on-aws-training
AWS Role - Based

DevOps Engineering on AWS

Learn how to use the most common DevOps patterns to develop, deploy and maintain applications on AWS.
ILT VILT
Course Duration 3 Days
Fees $550.00
aws-arc-architecting-on-aws-training
AWS Role - Based

Architecting on AWS

From this course, you will learn how to optimize the AWS Cloud by understanding how AWS services fit into cloud-based solutions.
ILT VILT
Course Duration 3 Days
Fees $550.00
img-get-info.jpg

Ready to Take Your Business from Great to Awesome?

Level-up by partnering with Trainocate. Get in touch today.

Name
Email
Phone
I'm inquiring for
Inquiry Details

By providing your contact details, you agree to our Privacy Policy.

Stay Connected. Be the first to Know.

Company

Vendors

Services

Customer Service

© Copyright Trainocate 2024. All rights reserved.