This is a self-paced lab that takes place in the Google Cloud console. The Cloud Natural Language API lets you extract entities, and perform sentiment and syntactic analysis on a block of text. In this hands-on lab you’ll learn how to extract entities and sentiment from text using the Cloud Natural Language API.

In this course, you will learn how to harness the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run data science workloads in the cloud. This is the fourth course in a five-course program that prepares you to take the DP-100: Designing and Implementing a Data Science Solution on Azurec ertification exam. The certification exam is an opportunity to prove knowledge and expertise operate machine learning solutions at a cloud-scale using Azure Machine Learning. This specialization teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Each course teaches you the concepts and skills that are measured by the exam. This Specialization is intended for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. It teaches data scientists how to create end-to-end solutions in Microsoft Azure. Students will learn how to manage Azure resources for machine learning; run experiments and train models; deploy and operationalize machine learning solutions, and implement responsible machine learning. They will also learn to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.

By the end of this project, you will have written LibreOffice Base queries to retrieve and aggregate data from a Sales database. Using both the Query Design tool and the SQL View you will group and summarize data using functions such as: Sum, Average, Count, Min and Max. Aggregating (grouping and summarizing) data can significantly increase its value when provided to users for use in analysis. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Data privacy controls how information is collected, used, shared, and disposed of, in accordance with policies or external laws and regulations. In this course, students will gain an understanding of what data privacy is along with how to identify and understand typical data protection and privatization objectives that an enterprise may have, and how to choose a data protection approach. The student will gain a background in multiple data privacy mechanisms and practices, and learn how to grow their data protection toolkit. The IBM DataFirst method will be the backbone of the discussion.

DevOps skills are in demand! DevOps skills are expected to be one of the fastest-growing skills in the workforce. This course can be a first step in obtaining those skills. Introduction to DevOps explores DevOps as a cultural movement, including building a business case for DevOps, the essentials of DevOps, and a brief history of DevOps. You will learn new ways of thinking, working, organizing, and measuring to fully gain the benefits of DevOps. You will learn how breaking down silos and organizing developers and operators into single cross-functional teams is necessary for truly adopting DevOps. Having everyone contributing and everyone being responsible for success is at the heart of DevOps. By thinking from a DevOps perspective, you will be able to build better products for your customer. You will view DevOps from a business perspective as well as for becoming a DevOps practitioner. You will see how building a culture of shared responsibility and transparency is the foundation of every high-performing DevOps teams. You will have an opportunity to explore the concepts of infrastructure for Continuous Integration and Continuous Delivery. You will be able to use actionable measures that apply directly to decision-making and will ultimately result in continuous improvement. This course is designed for those new to DevOps as well as those looking to increase their current knowledge of DevOps.

The Cyber Incident Response course will give students an understanding of how incidents are responded to at a high level, as well as allow them to build important technical skills through the hands-on labs and projects. This course starts with a high-level discussion of what happens at each phase of responding to an incident, followed by a technical deep dive into some of the more exciting parts of memory, network, and host analysis and forensics. This course is for anyone wishing to apply learned forensics and offensive knowledge such as ethical hacking to the incident response process.

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you add images and video to an application. You store files as objects in a Cloud Storage bucket.

Google Cloud Fundamentals: Core Infrastructure introduces important concepts and terminology for working with Google Cloud. Through videos and hands-on labs, this course presents and compares many of Google Cloud's computing and storage services, along with important resource and policy management tools.

The world of data has evolved and the advent of cloud technologies is providing new opportunities for businesses to explore. In this course, you will learn the various data platform technologies available, and how a Data Engineer can take advantage of this technology to an organization's benefit. This course part of a Specialization intended for Data engineers and developers who want to demonstrate their expertise in designing and implementing data solutions that use Microsoft Azure data services anyone interested in preparing for the Exam DP-203: Data Engineering on Microsoft Azure (beta). This is the first course in a program of 10 courses to help prepare you to take the exam so that you can have expertise in designing and implementing data solutions that use Microsoft Azure data services. The Data Engineering on Microsoft Azure exam is an opportunity to prove knowledge expertise in integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions that use Microsoft Azure data services. Each course teaches you the concepts and skills that are measured by the exam. By the end of this Specialization, you will be ready to take and sign-up for the Exam DP-203: Data Engineering on Microsoft Azure (beta).

By the end of this guided project, you will have successfully created an Azure account, logged into the Azure Portal and created, and configured a new Azure Cosmos DB Account, You will have created a Cosmos DB Database and Containers and imported sample data, tested the import by running queries against the database using a Cosmos DB Notebook. You will also have configured both Manual and autoscale throughput against Databases and individual containers and configured request units or RUs Having successfully configured throughput you will have made the database globally accessible by creating a Read replica in a different region thus providing near user access to the data and also high availability. You will have completed this project by then deleting any non required resources to keep costs to a minimum. If you enjoy this project, we recommend taking the Microsoft Azure Data Fundamentals DP-900 Exam Prep Specialization: https://www.coursera.org/specializations/microsoft-azure-dp-900-data-fundamentals