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Practical Data Science with Amazon SageMaker

Learning path

Build, train, and deploy machine learning models using Amazon SageMaker. This course covers key data science concepts, including data preprocessing, model selection, and optimization, while leveraging AWS’s scalable cloud-based tools. Ideal for data scientists, analysts, and developers, this learning path provides practical experience in applying machine learning to real-world problems with SageMaker’s powerful features. ~ 13 Hours.

What you'll learn

Deploy machine learning solutions in production environments using AWS and Azure platforms.
Implement data integration and analytics services on AWS for application development and large-scale data analysis.
Select, train, and evaluate machine learning models using AWS technology, including operationalizing models for production.

Learning path content

Complete the following content and you’ll be awarded a certified badge that you can proudly share with your network.

Amazon Web Services

Introduction to Machine Learning on AWS

Skills you'll gain: Machine Learning, Computer Vision, AWS SageMaker, Amazon Web Services, Deep Learning, Natural Language Processing, Generative AI Agents, Image Analysis, Text Mining, Data Processing, Artificial Intelligence and Machine Learning (AI/ML)

Whizlabs

AWS: Data Analytics

Skills you'll gain: Extract, Transform, Load, AWS Kinesis, AWS SageMaker, Data Processing, Apache Hadoop, Apache Hive, Data Integration, Data Pipelines, Serverless Computing, Data Lakes, Applied Machine Learning, Business Intelligence, Big Data, Amazon Web Services, Apache Spark, Real Time Data

Duke University

MLOps Platforms: Amazon SageMaker and Azure ML

Skills you'll gain: MLOps (Machine Learning Operations), Amazon S3, Microsoft Azure, Exploratory Data Analysis, Serverless Computing, Machine Learning, Cloud Solutions, AWS SageMaker, Data Pipelines, Python Programming, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Algorithms, Amazon Web Services, Machine Learning Methods, Feature Engineering, Data Analysis, Cloud Engineering, Applied Machine Learning