Digital Classroom - Practical Data Science with Amazon SageMaker

Resumen

Artificial intelligence and machine learning (AI/ML) are now widespread, and this course immerses students in the daily life of a data scientist. You'll collaborate effectively with data scientists and develop applications that integrate with ML.

Learn how data scientists create ML solutions on Amazon Web Services (AWS) using Amazon SageMaker. Experience the complete lifecycle of building, training, and deploying an ML model through instructor-led demonstrations and labs.

Course Objectives

• Discuss the benefits of different types of machine learning for addressing business challenges.
• Describe the standard processes, roles, and responsibilities of a team developing and deploying ML systems.
• Explain how data scientists utilize AWS tools and ML to resolve typical business issues.
• Summarize the data preparation steps undertaken by a data scientist.
• Overview the model training steps followed by a data scientist.
• Outline the steps for evaluating and tuning ML models.
• Detail the process of deploying a model to an endpoint and making predictions.
• Identify the challenges associated with operationalizing ML models.
• Match AWS tools with their respective ML functions.

This course is intended for:

• Development Operations (DevOps) engineers
• Application developers

Prerequisites

• AWS Technical Essentials
• Basic knowledge of Python programming
• Basic understanding of statistics

Course Outline

• Course Welcome
• Module 1:

  Introduction to Machine Learning

• Module 2:

  Preparing a Dataset

• Module 3:

  Training a Model

• Module 4:

  Evaluating and Tuning a Model

• Module 5:

  Deploying a Model

• Module 6:

  Operational Challenges

• Module 7:

  Other Model-Building Tools

• Course Summary and Resources

University:

Provider:

AWS Skill Builder

Categories:

Python Courses, Machine Learning Courses, Data Science Courses, Amazon Web Services (AWS) Courses, DevOps Courses, Amazon SageMaker Courses, Model Evaluation Courses, Model Training Courses, Data Preparation Courses, Model Deployment Courses

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