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Overview

Amazon SageMaker Studio helps data scientists prepare, build, train, deploy, and monitor machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML. This course prepares experienced data scientists to use the tools that are part of SageMaker Studio to improve productivity at every step of the ML lifecycle.
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What You'll Learn

  • Accelerate the preparation, building, training, deployment, and monitoring of ML solutions by using Amazon Sage Maker Studio.

Who Should Attend

  • Experienced data scientists who are proficient in ML and deep learning fundamentals. Relevant experience includes using ML frameworks, Python programming, and the process of building, training, tuning, and deploying models.
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Prerequisites

We recommend that all students complete the following AWS course prior to attending this course:

  • AWS Tech Essentials (1–day AWS instructor-led course)

We recommend students who are not experienced data scientists complete the following two courses followed by 1-year on-the-job experience building models prior to taking this course:

  • The Machine Learning Pipeline on AWS (4–day AWS instructor-led course)
  • Deep Learning on AWS (1–day AWS instructor-led course)

Learning Journey

Coming Soon...

Module 1: Amazon SageMaker Setup and Navigation

  • Launch SageMaker Studio from the AWS Service Catalog.
  • Navigate the SageMaker Studio UI.
  • Demo 1: SageMaker UI Walkthrough
  • Lab 1: Launch SageMaker Studio from AWS Service Catalog

Module 2: Data Processing

  • Use Amazon SageMaker Studio to collect, clean, visualize, analyze, and transform data.
  • Set up a repeatable process for data processing.
  • Use SageMaker to validate that collected data is ML ready.
  • Detect bias in collected data and estimate baseline model accuracy.
  • Lab 2: Analyze and Prepare Data Using SageMaker Data Wrangler
  • Lab 3: Analyze and Prepare Data at Scale Using Amazon EMR
  • Lab 4: Data Processing Using SageMaker Processing and the SageMaker Python SDK
  • Lab 5: Feature Engineering Using SageMaker Feature Store

Module 3: Model Development

  • Use Amazon SageMaker Studio to develop, tune, and evaluate an ML model against business objectives and fairness and explainability best practices.
  • Fine-tune ML models using automatic hyperparameter optimization capability.
  • Use SageMaker Debugger to surface issues during model development.
  • Demo 2: Autopilot
  • Lab 6: Track Iterations of Training and Tuning Models Using SageMaker Experiments
  • Lab 7: Analyze, Detect, and Set Alerts Using SageMaker Debugger
  • Lab 8: Identify Bias Using SageMaker Clarify

Module 4: Deployment and Inference

  • Use Model Registry to create a model group; register, view, and manage model versions; modify model approval status; and deploy a model.
  • Design and implement a deployment solution that meets inference use case requirements.
  • Create, automate, and manage end-to-end ML workflows using Amazon SageMaker Pipelines.
  • Lab 9: Inferencing with SageMaker Studio
  • Lab 10: Using SageMaker Pipelines and the SageMaker Model Registry with SageMaker Studio

Module 5: Monitoring

  • Configure a SageMaker Model Monitor solution to detect issues and initiate alerts for changes in data quality, model quality, bias drift, and feature attribution (explainability) drift.
  • Create a monitoring schedule with a predefined interval
  • Demo 3: Model Monitoring

Module 6: Managing SageMaker Studio Resources and Updates

  • List resources that accrue charges.
  • Recall when to shut down instances.
  • Explain how to shut down instances, notebooks, terminals, and kernels.
  • Understand the process to update SageMaker Studio.

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.

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Course Curriculum

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Exam & Certification

Frequently Asked Questions

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