In this 1-hour long project-based course, you will learn how to transform and search in arrays, how to use the map, filter and reduce methods and much more! This course is for beginners. A basic understanding of JavaScript (variables) or another programming language is required.

Microsoft certifications give you a professional advantage by providing globally recognized and industry-endorsed evidence of mastering skills in digital and cloud businesses.​​ In this course, you will prepare to take the DP-100 Azure Data Scientist Associate certification exam. You will refresh your knowledge of how to plan and create a suitable working environment for data science workloads on Azure, run data experiments, and train predictive models. In addition, you will recap on how to manage, optimize, and deploy machine learning models into production. You will test your knowledge in a practice exam​ mapped to all the main topics covered in the DP-100 exam, ensuring you’re well prepared for certification success. You will also get a more detailed overview of the Microsoft certification program and where you can go next in your career. You’ll also get tips and tricks, testing strategies, useful resources, and information on how to sign up for the DP-100 proctored exam. By the end of this course, you will be ready to sign-up for and take the DP-100 exam.​ This is the fifth course in a five-course program that prepares you to take the DP-100: Designing and Implementing a Data Science Solution on Azure certification 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.

Selenium automates browsers, that’s it. What you do with that power is up to you.” Selenium is the most widely used UI automation tool to test web applications. In this project, we are going to learn one of the most used concepts in selenium i.e identifying web elements using locating techniques provided by Selenium automation tool. By the end of this project, you will learn how to identify web elements using locators like Id, Name, Classname, Tagname, Linktext, Partial Linktext, XPath and CSS Selectors Special focus is given to XPath locator covering topics like absolute and relative XPath, methods, operators and axes in XPath, and how to write XPaths for dynamic web elements.

In this 2 hours long guided project you will learn how to create an e-commerce web UI wireframe using Pencil Project. You will create a user interaction and navigation flowchart, sketch re-usable items like header and navigation, group and arrange them into private collections, create home and product page, design dialogue and error messages, link the elements and finally export the prototype in an image, PDF or clickable interactive web format.

In this course, we look at Cloud, DevOps and the Linux operating system. The course material is a good for anyone preparing for the Linux Foundation Certified IT Associate (LFCA) exam or just interested in learning more about Linux. This course is the fourth course in a series that aims to prepare you for working as an information technology professional.

In this project, you will create a graphical user interface with a split pane that contains two panes. The first pane provides text fields to collect data on the number of students enrolled in English major, Mathematics major, and Chemistry major. In the second pane, there is a bar chart with the number of students in each major in the year 2020. When the button in the first pane is clicked, the bar chart will be updated with the number of students in each major in the year 2021.

In this project, you will write the HTML code to incorporate images and links into a web page. You will use a text editor called Notepad++ to write your code, and the Chrome browser to display the resulting web page. Since a website is often called upon to attract attention, images are an important part of the both the content and the layout of a web page. Knowing how to incorporate the image is just a part of the picture. There are also design and legal issues that come into play. Also critical to a website’s success is the ability to link from page to page or section to section. By then end of the course, you will have created a web page that includes an image and links—and even put them together to make an image link. 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.

In this hands-on project, we will build and train a simple artificial neural network model to detect spam/fake Instagram accounts. Fake and spam accounts are a major problem in social media. Many social media influencers use fake Instagram accounts to create an illusion of having so many social media followers. Fake accounts can be used to impersonate or catfish other people and be used to sell fake services/products. By the end of this project, you will be able to: - Understand the applications of Artificial Intelligence and Machine Learning techniques in the banking industry - Understand the theory and intuition behind Deep Neural Networks - Import key Python libraries, dataset, and perform Exploratory Data Analysis. - Perform data visualization using Seaborn. - Standardize the data and split them into train and test datasets. - Build a deep learning model using Keras with Tensorflow 2.0 as a back-end. - Assess the performance of the model and ensure its generalization using various Key Performance Indicators (KPIs). 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.

Scala is an expressive, versatile, and safe programming language. In this course, you will learn how to get the most out of Scala to solve common programming tasks such as modeling business domains, breaking down complex problems into simpler problems, manipulating data, or running parallel tasks. Along the journey, you will also learn the best practices for writing high-quality code that scales to large applications, how to handle errors, how to write tests, and how to leverage a productive development environment. This comprehensive, hands-on, course aims at leveling up your programming skills by embracing both functional programming and object-oriented programming. You will become familiar with the standard library and the common patterns of code used in the real world. Each week contains about 1h30 of video lectures. Each lecture is a ~10 min video focused on a specific skill or concept. We always start by looking at concrete problems, and then explain how language features or libraries make you more productive to solve these problems in general. Lectures are generally followed by a quiz to assess your progress. At the end of each week, a graded assignment inspired by real-world applications will give you an opportunity to put things in practice. The course covers Scala 3, and it mentions the differences with Scala 2.

In this one-hour project, you will learn how to use Microsoft Azure Cloud Platform and its Kubernetes Service to deploy a Web Application in a high availability environment, using the power of containers and Kubernetes in a real-world use case. Once you're done with this project, you will be able to clone a project, create a docker container image and deploy this container like a Kubernetes POD using the Azure Kubernetes Services with just a few steps.