Skip to main content

AWS Certified Cloud Practitioner

Written by Annika Thiemann on . Posted in AWS Training, Certifications, Training.

Who should take this exam?

This certification is intended for candidates who may be:

  • From a non-IT background and exploring a career in the AWS Cloud
  • In sales/marketing/business analyst roles looking to communicate more effectively with stakeholders and customers about the AWS Cloud
  • In on-premises IT or cloud roles, but new to AWS Cloud, and need a primer before diving into role-based AWS Certification(s)

Prerequisites

To earn this certification, you will need to take and pass the AWS Certified Cloud Practitioner exam. The exam features a combination of two question formats: multiple choice and multiple response. Additional information, such as a detailed exam content outline, is in the exam guide.

Recommended Training

Cloud Practitioner Essentials

Test

AWS Certified Cloud Practitioner exam

Recertification

AWS Certifications are valid for three years. To maintain your AWS Certified status, we require you to periodically demonstrate your continued expertise though a process called recertification. Recertification helps strengthen the overall value of your AWS Certification and shows individuals and employers that your credential covers the latest AWS knowledge, skills, and best practices.

Recertification for Foundational-Certification

Take the “Cloud Practitioner” exam

You can take the current AWS Certified Cloud Practitioner exam for recertification. You can use your 50% discount voucher from the Benefits section of your AWS Certification account to re-certify, or use it for any future certification exams you want to take.

Obtain an Associate or Professional certification

You can fulfill the recertification requirement by taking any Associate or Professional exam.

Building Streaming Data Analytics Solutions on AWS

Written by Gemma Corrado on . Posted in AWS Training, Training.

Building Streaming Data Analytics Solutions on AWS

current course dates can be found at the bottom of this page … company training available on request!

Course description

In this course, you will learn to build streaming data analytics solutions using AWS services, including Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK). Amazon Kinesis is a massively scalable and durable real-time data streaming service. Amazon MSK offers a secure, fully managed, and highly available Apache Kafka service. You will learn how Amazon Kinesis and Amazon MSK integrate with AWS services such as AWS Glue and AWS Lambda. The course addresses the streaming data ingestion, stream storage, and stream processing components of the data analytics pipeline. You will also learn to apply security, performance, and cost management best practices to the operation of Kinesis and Amazon MSK.

 

Course objectives

In this course, you will learn to:

  • Understand the features and benefits of a modern data architecture. Learn how AWS streaming services fit into a modern data architecture
  • Design and implement a streaming data analytics solution
  • Identify and apply appropriate techniques, such as compression, sharding, and partitioning, to optimize data storage
  • Select and deploy appropriate options to ingest, transform, and store real-time and near real-time data
  • Choose the appropriate streams, clusters, topics, scaling approach, and network topology for a particular business use case
  • Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights
  • Secure streaming data at rest and in transit
  • Monitor analytics workloads to identify and remediate problems
  • Apply cost management best practices

Intended audience

This course is intended for:

  • Data engineers and architects
  • Developers who want to build and manage real-time applications and streaming data analytics solutions

Prerequisites

We recommend that attendees of this course have:

  • At least one year of data analytics experience or direct experience building real-time applications or streaming analytics solutions. We suggest the Streaming Data Solutions on AWS whitepaper for
    those that need a refresher on streaming concepts.
  • Completed either Architecting on AWS or Data Analytics Fundamentals
  • Completed Building Data Lakes on AWS

Activities

This course includes:

  • presentations
  • practice labs
  • discussions
  • class exercises

Course duration / Price

  • 1 Day
  • € 750.00 (excl. tax) per person (DE)

Course outline

This course covers the following concepts:

Module A: Overview of Data Analytics and the Data Pipeline

  • Data analytics use cases
  • Using the data pipeline for analytics

Module 1: Using Streaming Services in the Data Analytics Pipeline

  • The importance of streaming data analytics
  • The streaming data analytics pipeline
  • Streaming concepts

Module 2: Introduction to AWS Streaming Services

  • Streaming data services in AWS
  • Amazon Kinesis in analytics solutions
  • Demonstration: Explore Amazon Kinesis Data Streams
  • Practice Lab: Setting up a streaming delivery pipeline with Amazon Kinesis
  • Using Amazon Kinesis Data Analytics
  • Introduction to Amazon MSK
  • Overview of Spark Streaming

Module 3: Using Amazon Kinesis for Real-time Data Analytics

  • Exploring Amazon Kinesis using a clickstream workload
  • Creating Kinesis data and delivery streams
  • Demonstration: Understanding producers and consumers
  • Building stream producers
  • Building stream consumers
  • Building and deploying Flink applications in Kinesis Data Analytics
  • Demonstration: Explore Zeppelin notebooks for Kinesis Data Analytics
  • Practice Lab: Streaming analytics with Amazon Kinesis Data Analytics and Apache Flink

Module 4: Securing, Monitoring, and Optimizing Amazon Kinesis

  • Optimize Amazon Kinesis to gain actionable business insights
  • Security and monitoring best practices

Module 5: Using Amazon MSK in Streaming Data Analytics Solutions

  • Use cases for Amazon MSK
  • Creating MSK clusters
  • Demonstration: Provisioning an MSK Cluster
  • Ingesting data into Amazon MSK
  • Practice Lab: Introduction to access control with Amazon MSK
  • Transforming and processing in Amazon MSK

Module 6: Securing, Monitoring, and Optimizing Amazon MSK

  • Optimizing Amazon MSK
  • Demonstration: Scaling up Amazon MSK storage
  • Practice Lab: Amazon MSK streaming pipeline and application deployment
  • Security and monitoring
  • Demonstration: Monitoring an MSK cluster

Module 7: Designing Streaming Data Analytics Solutions

  • Use case review
  • Class Exercise: Designing a streaming data analytics workflow

Module B: Developing Modern Data Architectures on AWS

  • Modern data architectures

 

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our trainings. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
Course language is German, on request also in English.

Authoring Visual Analytics Using Amazon QuickSight

Written by Gemma Corrado on . Posted in AWS Training, Training.

Authoring Visual Analytics Using Amazon QuickSight

current course dates can be found at the bottom of this page … company training available on request!

Course description

In this course, you will build a data visualization solution using Amazon QuickSight. QuickSight allows everyone in your organization to understand your data by exploring through interactive dashboards, asking questions in natural language, or automatically looking for patterns and outliers powered by machine learning. This course focuses on connecting to data sources, building visuals, designing interactivity, and creating calculations. You will learn how to apply security best practices to your analyses. You will also explore the machine learning capabilities built into QuickSight.

Course objectives

In this course, you will learn to:

  • Explain the benefits, use cases, and key features of Amazon QuickSight
  • Design, create, and customize QuickSight dashboards to visualize data and extract business insights from it
  • Select and configure appropriate visualization types to identify, explore, and drill down on business insights
  • Describe how to use one-click embed to incorporate analytics into applications
  • Connect, transform, and prepare data for dashboarding consumption
  • Perform advanced data calculations on QuickSight analyses
  • Describe the security mechanisms available for Amazon QuickSight
  • Apply fine-grained access control to a dataset
  • Implement machine learning on data sets for anomaly detection and forecasting
  • Explain the benefits and key features of QuickSight Q to enhance the dashboard user experience

Intended audience

This course is intended for:

  • Data and business analysts who build and manage business analytics dashboards

Prerequisites

Students with a minimum one-year experience authoring visual analytics will benefit from this course. We recommend that attendees of this course have:

  • Completed Data Analytics Fundamentals

Activities

This course includes:

  • presentations
  • demonstrations
  • group exercises
  • practice and challenge labs

Course duration / Price

  • 2 days
  • € 1,295.00 (excl. tax) per person (DE)

Course outline

This course covers the following concepts:

Day 1:

Module 1: Introduction and Overview of Amazon QuickSight

  • Introducing Amazon QuickSight
  • Why use Amazon QuickSight for data visualization

Module 2: Getting Started with Amazon QuickSight

  • Interacting with Amazon QuickSight
  • Loading data into Amazon QuickSight
  • Visualizing data in Amazon QuickSight
  • Demonstration: Walkthrough of Amazon QuickSight interface
  • Practice Lab: Create your first dashboard

Module 3: Enhancing and Adding Interactivity to Your Dashboard

  • Enhancing your dashboard
  • Demonstration: Optimize the size, layout, and aesthetics of a dashboard
  • Enhancing visualizations with interactivity
  • Demonstration: Walkthrough of dashboard interactivity features
  • Practice Lab: Enhancing your dashboard

Module 4: Preparing Datasets for Analysis

  • Working with datasets
  • Demonstration: Transform your datasets for analysis
  • Practice Lab: Preparing data for analysis

Module 5: Performing Advanced Data Calculations

  • Transform data using advanced calculations
  • Practice Lab: Performing advanced data calculations
  • Activity: Designing a Visual Analytics Solution

Day 2:

Module 6: Overview of Amazon QuickSight Security and Access Control

  • Overview of Amazon QuickSight security and access control
  • Dataset access control in Amazon QuickSight
  • Lab: Implementing access control in Amazon QuickSight visualizations

Module 7: Exploring machine learning capabilities

  • Introducing Machine Learning (ML) insights
  • Natural Language Query with QuickSight Q
  • Demonstration: Using QuickSight Q
  • Lab: Using machine learning for anomaly detection and forecasting

End of day challenge labs

  • Join data sources together
  • Create a dashboard
  • Enhance the dashboard and add interactivity
  • Perform advanced data calculations
  • Integrate machine learning tools into the dashboard

 

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our trainings. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
Course language is German, on request also in English.

AWS Security Best Practices

Written by Gemma Corrado on . Posted in AWS Training, Training.

AWS Security Best Practices

current course dates can be found at the bottom of this page … company training available on request!

Course description

Currently, the average cost of a security breach can be upwards of $4 million. AWS Security Best Practices provides an overview of some of the industry best practices for using AWS security and control types. This course helps you understand your responsibilities while providing valuable guidelines for how to keep your workload safe and secure. You will learn how to secure your network infrastructure using sound design options. You will also learn how you can harden your compute resources and manage them securely. Finally, by understanding AWS monitoring and alerting, you can detect and alert on suspicious events to help you quickly begin the response process in the event of a potential compromise.

Course objectives

In this course, you will learn to:

  • Design and implement a secure network infrastructure
  • Design and implement compute security
  • Design and implement a logging solution

Intended audience

This course is intended for:

  • Solutions architects, cloud engineers, including security engineers, delivery and implementation engineers, professional services, and Cloud Center of Excellence (CCOE)

Prerequisites

We recommend that attendees of this course have completed the following:

Activities

This course includes:

  • Training with instructor
  • Practical exercises

Course duration / Price

  • 1 day / € 795.00 (excl. tax) per person (DE)

Course outline

This course covers the following concepts:

Module 1: AWS Security Overview

  • Shared responsibility model
  • Customer challenges
  • Frameworks and standards
  • Establishing best practices
  • Compliance in AWS

Module 2: Securing the Network

  • Flexible and secure
  • Security inside the Amazon Virtual Private Cloud (Amazon VPC)
  • Security services
  • Third-party security solutions

Lab 1: Controlling the Network

  • Create a three-security zone network infrastructure.
  • Implement network segmentation using security groups, Network Access Control Lists (NACLs), and public and private subnets.
  • Monitor network traffic to Amazon Elastic Compute Cloud (EC2) instances using VPC flow logs.

Module 3: Amazon EC2 Security

  • Compute hardening
  • Amazon Elastic Block Store (EBS) encryption
  • Secure management and maintenance
  • Detecting vulnerabilities
  • Using AWS Marketplace

Lab 2: Securing the starting point (EC2)

  • Create a custom Amazon Machine Image (AMI).
  • Deploy a new EC2 instance from a custom AMI.
  • Patch an EC2 instance using AWS Systems Manager.
  • Encrypt an EBS volume.
  • Understand how EBS encryption works and how it impacts other operations.
  • Use security groups to limit traffic between EC2 instances to only that which is encrypted.

Module 4: Monitoring and Alerting

  • Logging network traffic
  • Logging user and Application Programming Interface (API) traffic
  • Visibility with Amazon CloudWatch
  • Enhancing monitoring and alerting
  • Verifying your AWS environment

Lab 3: Security Monitoring

  • Configure an Amazon Linux 2 instance to send log files to Amazon CloudWatch.
  • Create Amazon CloudWatch alarms and notifications to monitor for failed login attempts.
  • Create Amazon CloudWatch alarms to monitor network traffic through a Network Address Translation (NAT) gateway

 

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our trainings. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
Course language is German, on request also in English.

AWS Cloud for Finance Professionals

Written by Gemma Corrado on . Posted in AWS Training, Training.

AWS Cloud for Finance Professionals

current course dates can be found at the bottom of this page … company training available on request!

Course description

In this course, you will learn how finance professionals can use Amazon Web Services (AWS) to adopt cloud in a fiscally responsible manner. You will gain foundational knowledge to help you manage, optimize, and plan cloud spend. You will learn how to influence your organization’s builders to be more accountable and cost conscious. Finally, you will consider how you can use AWS to innovate in your finance organization.

Course objectives

In this course, you will learn to:

  • Define cloud business value
  • Estimate costs associated with current and future cloud workloads
  • Use tools to report, monitor, allocate, optimize, and plan AWS spend
  • Optimize cloud spending and usage through pricing models
  • Establish best practices with Cloud Financial Management (CFM) and Cloud Financial Operations (Cloud FinOps)
  • Implement financial governance and controls
  • Drive finance organization innovation

Intended audience

This course is intended for:

  • enterprise finance stakeholders who want to learn how to maximize cloud business value, use CFM best practices, and help finance teams innovate with AWS.

Prerequisites

We recommend that attendees of this course have:

Activities

This course includes:

  • presentations
  • hands-on labs
  • demonstrations

Course duration / Price

  • 2 days / € 1,250.00 (excl. tax) per person (DE)

Course outline

Day 1
Module 1: Introduction

  • Cloud spending decisions
  • AWS pricing
  • Cost drivers
  • AWS Well-Architected Framework
  • AWS Cloud Value Framework
  • Activity 1.1: Cloud value metrics
  • Cloud Financial Management
  • Activity 1.2: Cloud Financial Management outcomes

Module 2: Planning and Forecasting

  • Estimate cloud workload costs
  • Activity 2.1: Build and refine a cost estimate
  • Budget and forecast cloud costs
  • Improve cloud financial predictability

Module 3: Measurement and Accountability

  • KPIs and unit metrics
  • Cost visibility and monitoring
  • Demonstration 3.1: Tools for cost visibility, tools for cost monitoring
  • Cost allocation and accountability
  • Cost allocation building blocks

Day 2
Module 4: Cost Optimization

  • Usage optimizations
  • Commitment-based purchase options
  • Activity 4.1: Cost optimization

Module 5: Cloud Financial Operations

  • Organizational change for CFM
  • Organization models for CFM
  • Activity 5.1: Organizational models
  • Establish a cost-aware organizational culture
  • Governance, control, and agility
  • AWS governance and control building blocks
  • Automated-based governance using AWS services

Module 6: Financial Transformation and Innovation

  • Keys to financial innovation
  • Financial transformation
  • Activity 6.1: Solutions for financial innovation

Module 7: Resources and Next Steps

  • Module resources
  • Next steps

IMPORTANT: Please bring your notebook (Windows, Linux or Mac) to our trainings. If this is not possible, please contact us in advance.

Course materials are in English, on request also in German (if available).
Course language is German, on request also in English.