This course teaches computer programming to those with little to no previous experience. It uses the programming system and language called MATLAB to do so because it is easy to learn, versatile and very useful for engineers and other professionals. MATLAB is a special-purpose language that is an excellent choice for writing moderate-size programs that solve problems involving the manipulation of numbers. The design of the language makes it possible to write a powerful program in a few lines. The problems may be relatively complex, while the MATLAB programs that solve them are relatively simple: relative, that is, to the equivalent program written in a general-purpose language, such as C++ or Java. As a result, MATLAB is being used in a wide variety of domains from the natural sciences, through all disciplines of engineering, to finance, and beyond, and it is heavily used in industry. Hence, a solid background in MATLAB is an indispensable skill in today’s job market. Nevertheless, this course is not a MATLAB tutorial. It is an introductory programming course that uses MATLAB to illustrate general concepts in computer science and programming. Students who successfully complete this course will become familiar with general concepts in computer science, gain an understanding of the general concepts of programming, and obtain a solid foundation in the use of MATLAB. Students taking the course will get a MATLAB Online license free of charge for the duration of the course. The students are encouraged to consult the eBook that this course is based on. More information about these resources can be found on the Resources menu on the right.

The Unordered Data Structures course covers the data structures and algorithms needed to implement hash tables, disjoint sets and graphs. These fundamental data structures are useful for unordered data. For example, a hash table provides immediate access to data indexed by an arbitrary key value, that could be a number (such as a memory address for cached memory), a URL (such as for a web cache) or a dictionary. Graphs are used to represent relationships between items, and this course covers several different data structures for representing graphs and several different algorithms for traversing graphs, including finding the shortest route from one node to another node. These graph algorithms will also depend on another concept called disjoint sets, so this course will also cover its data structure and associated algorithms.

In this 2-hour long project-based course, you will learn how to create an interactive story game with the leading open source interactive fiction development platform Twine. You will learn how to create an interactive detective story, setting up variables, creating character sheet, inventory and clues, rolling dice and incorporating an RPG-style fighting mechanism. 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.

Machine learning (ML) is one of the fastest growing areas in technology and a highly sought after skillset in today’s job market. The World Economic Forum states the growth of artificial intelligence (AI) could create 58 million net new jobs in the next few years, yet it’s estimated that currently there are 300,000 AI engineers worldwide, but millions are needed. This means there is a unique and immediate opportunity for you to get started with learning the essential ML concepts that are used to build AI applications – no matter what your skill levels are. Learning the foundations of ML now, will help you keep pace with this growth, expand your skills and even help advance your career. This course will teach you how to get started with AWS Machine Learning. Key topics include: Machine Learning on AWS, Computer Vision on AWS, and Natural Language Processing (NLP) on AWS. Each topic consists of several modules deep-diving into variety of ML concepts, AWS services as well as insights from experts to put the concepts into practice.

This Guided Project "Continuous Delivery and Release Pipelines with Azure DevOps" is for IT professionals who want to raise the quality of their software products to a higher level by totally automating their software applications’ deployment processes. In this 1-hour long project-based course, you will learn how to use Azure DevOps Services to safely deploy new software version to the environments in the Microsoft’s cloud called Azure. Since this project uses Azure DevOps Services, you will need access to an Azure DevOps account. In the video at the beginning of the project you will be given instructions on how to sign up for one. Besides that, you need to have a valid account on Microsoft Azure and a Resource group which will be used across this guided project, so you will need to have that prepared before you begin. If you are ready to start automating deployment process of your applications, then this project is for you! Let’s get started!

Ongoing and proactive management is critical to the security and performance of database management systems. Database administration is the function of managing the operational aspects of database systems and maintaining them. Database administrators work to ensure that applications make the most efficient use of databases and that physical resources are used adequately and efficiently. In this course, you will discover some of the activities, techniques, and best practices for managing a database. You will learn about configuring and upgrading database server software and related products. You will also learn about database security; how to implement user authentication, assign roles, and assign object-level permissions. You will also gain an understanding of how to perform backup and restore procedures in case of system failures. You will learn about how to optimize databases for performance, monitor databases, collect diagnostic data, and access error information to help you resolve issues that may occur. Many of these tasks are repetitive, so you will learn how to schedule maintenance activities and regular diagnostic tests and send automated messages of the success or failure of a task.

One of the biggest challenges QAs and Developers face in test automation is synchronizing application under test and test automation code. Selenium provides multiple wait methods (like Implicit and Explicit waits) to synchronize the application under test and test automation code. In this two hours guided project, through hands-on, practical experience, you will go through concepts using Page load timeout, usage of implicit, explicit and Fluent waits.

In this 2-hour long project-based course, you will learn how to train an Object Detection Model using Facebook's Detectron2. Detectron2 is a research platform and a production library for deep learning, built by Facebook AI Research (FAIR). We will be building an Object Detection Language Identification Model to identify English and Hindi texts written which can be extended to different use cases. We will look at the entire cycle of Model Development and Evaluation in Detectron2. We will first look at how to load a dataset, visualize it and prepare it as an input to the Deep Learning Model. We will then look at how we can build a Faster R-CNN model in Detectron2 and customize it. We will then configure the parameters & hyperparameters of the model. We will then move on to training the Model and subsequently to model inference and evaluation. 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.

This is a self-paced lab that takes place in the Google Cloud console. In this lab you use Cloud Functions and Pub/Sub to create an end-to-end document processing pipeline using Document AI. The Document AI API is a document understanding solution that takes unstructured data, such as documents and emails, and makes the data easier to understand, analyze, and consume. In this lab, you will create a document processing pipeline that will automatically process documents that are uploaded to Cloud Storage. The pipeline consists of a primary Cloud Function that processes new files that are uploaded to Cloud Storage using a Document AI form processor and then saves form data detected in those files to BigQuery. If the form data includes any address fields the address data is then written to a Pub/Sub topic that in turn triggers a second Cloud Function that uses to Geocoding API to provide geographic coordinate data for the address that is also written to BigQuery. This is a simple pipeline that uses a general form processor that will detect basic form data, such as a labelled field containing address information. Document AI processors that use one of the specialized parsers that are beyond the scope of this lab provide enhanced entity information for specific document types even when those documents do not include labelled fields. For example, a Document AI Invoice parser can provide detailed address and supplier information, from an unlabelled invoice document because it understands the layout of invoices.

Amazon famously delivers new code every 11.6 seconds. Just a few years ago, this was unthinkable: many ‘cutting edge’ firms would release software quarterly. When it comes to digital innovation, velocity is critical and many would say it’s the most reliable determinant of success. Bringing an organization to the state of the art (or even functional capability) in this area requires strong work in a combination of disciplines and a combination of both technical and managerial skills. There is no single cookie-cutter approach for achieving this capability. Much like agile, the right focus and formulation depends a lot on the facts and circumstances of the team. This course, developed at the Darden School of Business at the University of Virginia and taught by top-ranked faculty, will provide you with the interdisciplinary skill set to cultivate a continuous deployment capability in your organization. After completing this course, you will be able to: 1. Diagnose a team’s delivery pipeline and bring forward prioritized recommendations to improve it 2. Explain the skill sets and roles involved in DevOps and how they contribute toward a continuous delivery capability 3. Review and deliver automation tests across the development stack 4. Explain the key jobs of system operations and how today’s leading techniques and tools apply to them 5. Explain how high-functioning teams use DevOps and related methods to reach a continuous delivery capability 6. Facilitate prioritized, iterative team progress on improving a delivery pipeline