hands-on lab

AI Engineer L6 M1 Workshop Day 1 Lab

Difficulty: Intermediate
Duration: Up to 6 hours
Students: 32
You can pause this lab for up to 30m
On average, students complete this lab in55m
Get guided in a real environmentPractice with a step-by-step scenario in a real, provisioned environment.
Learn and validateUse validations to check your solutions every step of the way.
See resultsTrack your knowledge and monitor your progress.

Description

 

The Amazon SageMaker helps in setting up and deploying a machine learning model that utilises a graphics processing unit (GPU) involves an initial configuration and the establishment of specific environment variables to maximize the advantages of NVIDIA GPUs. Nevertheless, configuring the environment to ensure compatibility with SageMaker on the Amazon Web Services (AWS) cloud can be a lengthy process.

 

In this lab you will explore how even a small data exploration can prompt meaningful business insights, guiding the conversation towards potential GenAI solutions.

Covered topics

Hands-on Lab UUID

Lab steps

0 of 3 steps completed.Use arrow keys to navigate between steps. Press Enter to go to a step if available.
  1. Logging In to the Amazon Web Services Console
  2. Launching Jupyter Lab on SageMaker Notebook
  3. Open an Empty Lab Jupyter Notebook and Execute the Instructions