Data is one of an organization’s most valuable commodities. But how can organizations best use their data? And how does the organization determine which data is the most recent, accurate, and useful for business decision making at the highest level? After taking this course, you will be able to describe different kinds of repositories including data marts, data lakes, and data reservoirs, and explain their functions and uses. A data warehouse is a large repository of data that has been cleaned to a consistent quality. Not all data repositories are used in the same way or require the same rigor when choosing what data to store. Data warehouses are designed to enable rapid business decision making through accurate and flexible reporting and data analysis. A data warehouse is one of the most fundamental business intelligence tools in use today, and one that successful Data Engineers must understand. You will also be able to describe how data warehouses serve a single source of data truth for organization’s current and historical data. Organizations create data value using analytics and business intelligence applications. Now that you have experienced the ELT process, gain hands-on analytics and business intelligence experience using IBM Cognos and its reporting, dashboard features including visualization capabilities. Finally, you will complete a shareable final project that enables you to demonstrate the skills you acquired in each module.

This is a self-paced lab that takes place in the Google Cloud console. This lab demonstrates how optimization in your cluster's workloads can lead to an overall optimization of your resources and costs. It walks through a few different workload optimization strategies such as container-native load balancing, application load testing, readiness and liveness probes, and pod disruption budgets.

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will learn how to secure multi-cloud applications using Identity-Aware Proxy (IAP) connector.

Welcome to Systems and Application Security Course! In the Systems and Application Security Course, you will gain an understanding of computer code that can be described as harmful or malicious. Both technical and non-technical attacks will be discussed. You will learn how an organization can protect itself from these attacks. You will learn concepts in endpoint device security, cloud infrastructure security, securing big data systems, and securing virtual environments. Objectives 1. Identify malicious code activity 2. Describe malicious code and the various countermeasures 3. Describe the processes for operating endpoint device security 4. Define mobile device management processes 5. Describe the process for configuring cloud security 6. Explain the process for securing big data systems 7. Summarize the process for securing virtual environments

Do you want to learn about developing applications that are cloud native right from conception to implementation? In this course, you’ll begin with some crucial cloud concepts. Then, you will dive into specific tools and techniques for developing cloud native apps. Learning about the Cloud Native Computing Foundation, the significance of hybrid cloud infrastructures, and how they affect cloud app developers will be covered You will then look at two key areas of cloud thinking: modernization and continuous integration/continuous delivery.

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you create a Cloud Composer environment using the GCP Console. You then use the Airflow web interface to run a workflow that verifies a data file, creates and runs an Apache Hadoop wordcount job on a Dataproc cluster, and deletes the cluster.

Hello everyone and welcome to this new hands-on project on Machine Learning Regression with Amazon Web Services (AWS) AutoGluon. In this project, we will train several regression models using a super powerful library known as AutoGluon. AutoGluon is the library behind AWS SageMaker autopilot and it allows for quick prototyping of several powerful models using a few lines of code.

By the end of this project, you will have successfully created an Azure account, logged into the Azure Portal, created a Speech Cognitive Services resource and use it in a C# console application by executing API calls to generate predictions. You will learn to execute API calls to the pre-built Computer Vision resource through a series of tasks which include creating the appropriate resource to realize the API calls and then building a simple C# console application with Visual Studio Community that will execute speech-to-text in different languages. The skills learned in this guided project will provide the foundation to understanding and implementing Artificial Intelligence & Machine Learning solutions in Microsoft Azure. If you enjoy this project, we recommend taking the Microsoft Azure AI Fundamentals AI-900 Exam Prep Specialization: https://www.coursera.org/specializations/microsoft-azure-ai-900-ai-fundamentals

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you learn how to use Google Cloud Storage Bucket Lock to manage object retention.

Welcome to "Accessing your AWS EC2 servers". In this guided project you will learn various methods to access your AWS EC2 servers. The task-based approach that we follow in our guided project will get you a better understanding of accessing your EC2 servers using pem file, EC2 Instance Connect, SSM etc. This comes very handy while working on your real-life project on AWS Cloud. Good luck as you get started, and I hope you enjoy the course! Happy learning !!!!!