Seminare zum Thema Cloudcomputing

Overview

Learn the key features to connect applications and create workflows with webMethods Integration SaaS. With this training you will expand beyond the basics of webMethods Integration. This is a course includes hands-on exercises to build needed skills and become self-sufficient with webMethods Integration SaaS. 

If you have any questions about this course, or if you would like to register your interest to attend this class, please contact ibmlearning@ibm.com.

In this course, you will learn to:

• Explain the cost of core AWS services
• Determine and estimate costs associated with current and future cloud workloads
• Use strategies and best practices to reduce AWS costs
• Use AWS tools to manage, monitor, alert, and optimize your AWS spend
• Apply strategies to monitor service costs and usage
• Implement governance standards, including resource tagging, account structure, provisioning, permissions, and access

• Die Rolle der Informationstechnologie (IT) in einer Organisation bei der Umgestaltung von Unternehmen
• Der Kundennutzen durch das branchenübergreifende Verwenden der Cloud
• Das Cloud-Geschäftsmodell
• Wichtige Sicherheitspraktiken des Cloud Computing
• Und vieles mehr

In this course, you will explore:

• Workload definition and key concepts
• The AWS Well-Architected Framework Review phases, process, best practices, and anti-patterns
• High and medium risks
• Prioritizing improvements to the AWS Well-Architected workflow
• Locating and using the AWS Well-Architected Framework white paper, labs, prebuilt solutions in the AWS solutions library, AWS Well-Architected independent software vendors (ISVs), and AWS Well-Architected Partner Program (WAPP)

• Anwenden von Datenbankkonzepten, Datenbankmanagement und Methoden zur Datenmodellierung
• Evaluieren des Hostings von Datenbanken auf Amazon EC2-Instances
• Evaluieren relationaler AWS-Datenbankservices und ihrer Funktionen (Amazon RDS, Amazon Aurora und Amazon Redshift)
• Evaluieren nicht-relationaler AWS-Datenbankservices und ihrer Funktionen (Amazon DocumentDB, Amazon DynamoDB, Amazon ElastiCache, Amazon Neptune und Amazon QLDB)
• Und vieles mehr

In this course, learn how to solve a real-world use case with machine learning and produce actionable results using Amazon SageMaker. This course teaches you how to use Amazon SageMaker to cover the different stages of the typical data science process, from analyzing and visualizing a data set, to preparing the data and feature engineering, down to the practical aspects of model building, training, tuning and deployment. Was Sie in diesem Kurs lernen:

• Prepare a dataset for training.
• Train and evaluate a machine learning model.
• Automatically tune a machine learning model.
• Prepare a machine learning model for production.
• Think critically about machine learning model results.