Working with Big Data on AWS
The course provides a comprehensive overview of big data and machine learning (ML) technologies on Amazon Web Services (AWS). Students will learn to use AWS resources for data processing, analysis, and management, as well as implement machine learning solutions using AWS services such as SageMaker. Through hands-on lessons and guided labs, participants will gain hands-on skills to design, implement, and manage big data and machine learning infrastructures on AWS.
CODE: DSAI207
Category: Artificial Intelligence Course
DESCRIZIONE
COURSE CONTENT
COURSE OBJECTIVES
ADDITIONAL INFORMATION
DESCRIZIONE
Teaching methodology
The course includes educational laboratories in which each student will be able to carry out training exercises that will provide practical experience in the use of the tool, for each of the topics covered during the course.Prerequisites
- Familiar with the concept of Big Data
- Amazon AWS basic knowledge
COURSE CONTENT
Below is an overview of the course contents:
- Introduction to AWS services for big data: This module provides an overview of the services offered by Amazon Web Services (AWS) for the management and analysis of big data, introducing students to the main tools and concepts.
- Data Storage and Management on AWS: Here students will learn best practices for storing and managing data on AWS, using services like Amazon S3 and Amazon Glacier to ensure durability, data availability and security.
- Big Data Processing and Analysis on AWS: This module focuses on processing and analyzing large volumes of data on AWS, introducing students to services such as Amazon Redshift and Amazon EMR for distributed processing and data analysis.
- Using Amazon EMR and Athena for data analysis: Students will gain hands-on skills in using services like Amazon EMR (Elastic MapReduce) and Amazon Athena to perform data analysis in a scalable and efficient on AWS.
- Introduction to ML Concepts on AWS: This module introduces students to the fundamental concepts of machine learning on AWS, providing an overview of the services and tools available for development, training and deployment of machine learning models.
- Best Practices for Data Management and Security on AWS: Here students will explore best practices for data management and security on AWS, including concepts such as secure access, encryption and regulatory compliance.
- Monitoring and Maintenance of Big Data and Machine Learning Solutions on AWS: This module focuses on monitoring and maintaining big data and machine learning solutions on AWS, providing students with tools and techniques to ensure optimal performance and reliability of applications.
COURSE OBJECTIVES
At the end of the course, participants will be able to:
- Use big data services on AWS to store, process, and analyze data
- Implement machine learning models using services like SageMaker
- Manage and monitor big data and machine learning solutions on AWS
- Apply best practices for data management and security on AWS
ADDITIONAL INFORMATION
Duration – 1 day
Delivery – in the classroom, on site, remotely
PC and SW requirements:
- Internet connection
- Web browser, Google Chrome
- Zoom
- Instructor: Italian
- Laboratories: English
- Slides: English
ARTIFICIAL INTELLIGENCE COURSE CATALOG
ARTIFICIAL INTELLIGENCE COURSE CATALOG
