AWS Discovery Day – Cloud Practitioner Essentials & Machine Learning Basics

Ci trovate in Aula A1.02, Blocco A primo piano

In collaborazione con Claranet (AWS Training Partner) abbiamo organizzato due sessioni di formazione gratuita di base, saranno tenute in Italiano da Amazon Authorized Instructors.
È possibile partecipare anche a solo una delle due sessioni; vi chiediamo - per meglio organizzare la logistica - di segnalare durante la registrazione a quali volete partecipare.

09:30 - 12:30 Cloud Practitioner Essentials
14:30 - 16:30 Machine Learning Basics

AWS Discovery Day – Cloud Practitioner Essentials
This 3-hour session teaches to IT professional interested in Amazon Web Services (AWS) the benefits of computing in the cloud and how to improve business processes.
Key Learnings

• What the cloud is and how it works
• Benefits of the AWS Cloud
• Basic global infrastructure of the cloud
• Basic services and common use cases (computing, storage, networking, security, etc.)
• Shared responsibility model
• Basic concepts of security services and compliance

Contents
The AWS Discovery Day is designed to introduce to business owners and IT professionals the AWS cloud computing concepts and foundational infrastructure services.

Module 1: Introduction to the Cloud and AWS

• Benefits of cloud computing
• Cloud computing components
• Cloud computing deployment models

Module 2: Overview of AWS Services

• AWS core services and how to use them
• AWS service domains
• Compute
• Storage
• Database
• Networking and Content Delivery

Module 3: Security and Compliance Overview

• Overview of security
• Shared responsibility model
• AWS security services
• AWS compliance

Target audience

• Business Owners
• IT professionals
• Individuals interested in learning basic cloud concepts and AWS foundamental services

AWS Discovery Day – Machine Learning Basics
Are you interested in machine learning, but not sure where to start? Join us for this 2-hour session to learn the basic concepts and demystify the basics.
Key Learnings

• What is Machine Learning?
• What is the machine learning pipeline, and what are its phases?
• What is the difference between supervised and unsupervised learning?
• What is reinforcement learning?
• What is deep learning?

Contents
Using real-world examples, you’ll learn about important concepts, terminology, and the phases of a machine learning pipeline. Learn how you can unlock new insights and value for your business using machine learning.

Module 1: Machine learning basics

• Classical programming vs. machine learning approach
• What is a model?
• Algorithm features, weights, and outputs
• Machine learning algorithm categories
• Supervised algorithms
• Unsupervised algorithms
• Reinforcement learning

Module 2: What is deep learning?

• How does deep learning work?
• How deep learning is different

Module 3: The Machine Learning Pipeline

• Business problem
• Data collection and integration
• Data processing and visualization
• Feature engineering
• Model training and tuning
• Model evaluation
• Model deployment

Module 4: What are my next steps?

• Resources to continue learning

Target audience

• Developers
• Solution architects
• Data engineers
• Individuals interested in building solutions with machine learning - no machine learning experience required!