In this 2-hour long tutorial, you will learn how to create, and configure a Microsoft Azure Database for MySQL server and database. We will do this by walking through the process of creating a free trial subscription on Azure, logging in and getting familiar with the Azure Portal. We will create a Resource Group in preparation for creating the Azure database and then step through the process of configuring and deploying an Azure Database for MySQL server. From here we will connect securely to the cloud based server and create a new database. We will then populate the database with some sample data, query and update the data using the MySQL command line tool. Once complete we will restore the database to a point in time using the Azure restore database process and finally clean up unused resources keeping costs to a minimum. The skills learned in this guided project provide the foundation to understanding and implementing Azure Relational Databases specifically in relation to MySQL which is a fully managed database offering from Microsoft Azure. 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. 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

This course introduces you to one of the main types of modelling families of supervised Machine Learning: Regression. You will learn how to train regression models to predict continuous outcomes and how to use error metrics to compare across different models. This course also walks you through best practices, including train and test splits, and regularization techniques. By the end of this course you should be able to: Differentiate uses and applications of classification and regression in the context of supervised machine learning  Describe and use linear regression models Use a variety of error metrics to compare and select a linear regression model that best suits your data Articulate why regularization may help prevent overfitting Use regularization regressions: Ridge, LASSO, and Elastic net   Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience  with Supervised Machine Learning Regression techniques in a business setting.   What skills should you have? To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics.

Content creation and managing when it is created is key to business in the online world. Finding tools to manage your content calendar will help to make the job much easier. By the end of this project you will have a content creation calendar on Trello that makes it a breeze. 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.

Welcome to this project-based course, SQL CASE Statements. In this project, you will learn how to use SQL CASE statements to query tables in a database. By the end of this 2-hour long project, you will be able to write simple CASE statements to retrieve the desired result from a database. Then, we will move systematically to write more complex SQL CASE statements. Furthermore, we will see how to use the CASE clause together with aggregate functions, and SQL joins to get the desired result you want from tables in a database. Also, you will learn how to use the CASE clause to transpose the result of a query. Also, for this hands-on project, we will use PostgreSQL as our preferred database management system (DBMS). Therefore, to complete this project, it is required that you have prior experience with using PostgreSQL. Similarly, this project is an advanced SQL concept; so, a good foundation for writing SQL queries, and performing joins in SQL is vital to complete this project. If you are not familiar with writing queries in SQL and SQL joins and want to learn these concepts, start with my previous guided projects titled “Querying Databases using SQL SELECT statement", “Performing Data Aggregation using SQL Aggregate Functions” and “Mastering SQL Joins”. I taught these guided projects using PostgreSQL. So, taking these projects will give the needed requisite to complete this project on SQL CASE Statements. However, if you are comfortable writing queries in PostgreSQL, please join me on this wonderful ride! Let’s get our hands dirty!

Overview Robotic Process Automation (RPA) is reshaping the accounting and finance profession. 40% of transactional accounting work is expected to be automated by 2020 and predicted to touch 230 million knowledge workers, 9% of the global workforce, according to McKinsey Research. Driven by the need to stay competitive, decrease costs and increase efficiency, RPA is quickly making a significant impact on the profession. Companies no longer think about "if" but "when" to implement RPA. Short Description: • Robotic Process Automation (RPA) can transform business processes by eliminating the mundane, time-consuming, manual tasks that professionals complete; enabling them more time to focus on critical thinking. This course for accounting and finance professionals worldwide will show through use cases how robotic process automation can be utilized to decrease errors and increase productivity. Course description/ Overarching Learning Goal This course is intended to provide accounting and financial professionals with practical literacy on robotic process automation through a real-world, relevant data preparation use case. It will help identify potential uses and the benefits and considerations for robotic process automation. This course will help you make the business case by helping you assess requirements, define proof of value and measure and validate the ROI for automation.

Now more than ever, corporations are investing heavily in IT. The quality of these investments affect the daily work of millions, yet it’s not uncommon to see industry surveys where the failure rates for IT projects is over 50%. It’s possible to do better and it’s possible to do so consistently. In this two-week course, we’ll step through major challenges within corporate IT and how to address them with the disciplined use of design thinking, Lean Startup, and agile as a team framework. By the end of this course, developed at the Darden School of Business at the University of Virginia and taught by top-ranked faculty, you’ll be able to: Use the Business Model Canvas to focus your company strategy and facilitate buy-in from stakeholders Translate your work on the Canvas to specific charters in IT Rapidly prototype strategically-aligned processes for implementation within your IT infrastructure Please Note: This is a short-form course, two weeks in duration.

This is a self-paced lab that takes place in the Google Cloud console. In this lab, Deploy Cloud IDS (Intrusion Detection System), a next-generation advanced intrusion detection service that provides threat detection for intrusions, malware, spyware and command-and-control attacks, to simulate multiple attacks and view the threat details.

This course empowers you to develop scalable, performant LookML (Looker Modeling Language) models that provide your business users with the standardized, ready-to-use data that they need to answer their questions. Upon completing this course, you will be able to start building and maintaining LookML models to curate and manage data in your organization’s Looker instance.

In this course, we start with some services where the training model and raw inference is handled for you by Amazon. We'll cover services which do the heavy lifting of computer vision, data extraction and analysis, language processing, speech recognition, translation, ML model training and virtual agents. You'll think of your current solutions and see where you can improve these solutions using AI, ML or Deep Learning. All of these solutions can work with your current applications to make some improvements in your user experience or the business needs of your application.

By the end of this project, you will use a bash script to execute commands and observe their output on a Linux system. Bash, or Bourne Again Shell, is more than a shell running in a terminal on Linux; it is a programming language that is used to create powerful programs called shell scripts. Shell scripts are often used to capture common repetitive tasks so they can be executed without the need to memorize multiple individual commands.