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Virtual reality is changing the way we interact with the world. But how does it work, what hardware is involved, and how is software written for it? In this course, part of the Virtual Reality Professional Certificate program, we will explore the foundations of user-friendly virtual reality app development for consumers, as well as enterprise solutions. Both hardware and software aspects will be discussed. You will learn to evaluate devices necessary for virtual reality applications, what their differences are, how you write interactive applications for virtual reality, and we will discuss the most frequent problems you are going to need to solve to write virtual reality software. In this course, you will explore the basics of virtual reality software through copying and modifying JavaScript to explore tradeoffs in VR application design. Extensive programming experience is not required. By the end of this course, you will understand what is important for successful virtual reality software and learn how to write simple virtual reality programs themselves with WebVR. This course is taught by an instructor with almost two decades of experience in virtual reality who leads the Immersive Visualization Laboratory at UC San Diego.
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    In this course, you will learn how to quickly and easily get started with Artificial Intelligence using IBM Watson. You will understand how Watson works, become familiar with its use cases and real-life client examples, and be introduced to several Watson AI services from IBM that enable anyone to easily apply AI and build smart apps. You will also work with several Watson services including Watson studio, Watson assistant and Watson discovery to demonstrate AI in action. This course does not require any programming or computer science expertise and is designed for anyone whether you have a technical background or not.
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      The user experience is defined as the result of the internal states (eg expectations, predispositions) of a user, the characteristics of a system (eg complexity, usability) and the context of use of the interaction between the user and the system (eg in organization, in private). Organizations value innovative and well-designed user experiences for their customers and employees, whether they are using their websites, mobile applications, self-service kiosks in store, or various internal interfaces. The practice of UX design uses the user-centered approach and covers 3 main activities: UX research (getting to know the users and their contexts), activities surrounding ideation (such as "design thinking" and participatory design) and prototyping. This course teaches methods, techniques and digital tools specific to UX in today's business context. A UX professional is able to intervene in the design process of a digital product or service in order to ensure a user-centered approach. This allows the organization to respond to the expectations of its users. A UX professional mobilizes a range of interview and observation methodologies until the development of a prototyped interface. UXPA defines user experience professionals as specialists involved in research, design and evaluation of products and services. Conceptually, this notion of user experience emerges from the human-centered design approach in the field of human machine interaction and human factors in industrial engineering. Research corresponds to the activity of learning about user interfaces and the context in which they will be used. Evaluation corresponds to user observation when using these interfaces, as much before, during and after the design and development of the product. Design corresponds to the standards and principles of design of digital products or services offering optimal user experiences. Overall objective of the MOOC: Discuss what the user experience is in the context of business practice
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        As the Internet of Things (IoT) continues to grow so will the number of privacy and security concerns and issues. As a professional working in the field, it is essential to understand the potential security risks and how to best mitigate them. In this course, you will learn about security and privacy issues in IoT environments. We’ll explore the organizational risks posed by IoT networks, and the principles of IoT device vulnerabilities. We’ll also look at software and hardware IoT Applications for industry. With billions of devices tracking our every move, privacy is a critical issue. We will explore and discuss the social and commercial implications the IoT brings to society.
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          Want to produce and record your own music? This course will help you do that by showing you how to apply new technologies to your own creative practice, using freeware and browser based apps. Music Technology Foundations draws on Adelaide’s world-class pioneering expertise in making electronic music, to provide a great foundation to a career in music and to enable any learner to use technology in creative ways. In this course, you’ll learn about the core principles of music technology, including sound, audio, MIDI, effects and sequencing.
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            Improvements in modern biology have led to a rapid increase in sensitivity and measurability in experiments and have reached the point where it is often impossible for a scientist alone to sort through the large volume of data that is collected from just one experiment. For example, individual data points collected from one gene expression study can easily number in the hundreds of thousands. These types of data sets are often referred to as ‘biological big data’ and require bioinformaticians to use statistical tools to gain meaningful information from them. In this course, part of the Bioinformatics MicroMasters program, you will learn about the R language and environment and how to use it to perform statistical analyses on biological big datasets. This course is part of the Bioinformatics MicroMaster’s program from UMGC. Upon completion of the program and receipt of the verified MicroMaster’s certificate, learners may then transition into the full UMGC Master’s Program in Biotechnology with a specialization in Bioinformatics without any application process or testing. See the MicroMasters program page for more.
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              In this course, you will learn what AI is and understand its applications and use cases and how it is transforming our lives. You will explore basic AI concepts including machine learning, deep learning, and neural networks as well as use cases and applications of AI. You will be exposed to concerns surrounding AI, including ethics, bias, jobs and the impacts on society. You will take a glimpse of the future with AI, get advice for starting an AI related career, and wrap up the course by demonstrating AI in action with a mini project. This AI for Everyone course does not require any programming or computer science expertise and is designed to introduce the basics of AI to anyone whether you have a technical background or not.
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                Experimentation is a key capability for any business to develop and master. Learn how to leverage data to build knowledge and apply this knowledge to improve business outcomes and create strategic advantages. This course is part of both the Digital Product Management and Digital Leadership MicroMasters programs. In it, you will learn to develop iterative business experiments using agile methods. This capability is central to digital businesses as it allows them to sustain competitive advantage through both incremental improvements as well as significant, disruptive innovations when opportunities and conditions warrant them. This course focuses on experimentation across the three layers of a digital business: (1) the capacity of the technical infrastructure to provide an iterative and operational process that uses experiments to gather data and develop knowledge (2) the ability to use agile methods and manage the knowledge interfaces among experts at the organizational layer to derive insight from data to create knowledge and ultimately drive improvements in products and processes. (3) the capability to use the technical and organizational infrastructures to drive experimentation at scale in order to deliver digital transformation.
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                  JavaScript is the programming language of the World Wide Web. As a professional web software developer, you will not only need to know how to program in this simple yet powerful language, but you will need to understand the fundamentals of how data is exchanged on the World Wide Web (WWW) and what tools and frameworks are available to you for creating robust, interactive web applications. This course, part of the CS Essentials for Software Development Professional Certificate program, provides an introduction to modern web development using JavaScript. In addition to exploring the basics of web page creation using HTML and CSS, you will learn advanced web page layout and responsive design tools such as Bootstrap. You will also learn how browsers represent a web page data using the Document Object Model (DOM) and how to develop dynamic, interactive web pages using JavaScript in the browser. Beyond fundamental JavaScript syntax and advanced language features such as callbacks, events, and asynchronous programming, you will work with jQuery, which provides functionality for simplified DOM manipulation and event handling. This course will also introduce you to modern web frameworks and component-based libraries such as React.js for efficiently developing modular web page components, and D3.js for creating data-driven documents. We will also teach you how to represent and exchange data using JavaScript Object Notation (JSON), and how to access RESTful APIs on the web. Server-side JavaScript is becoming more prevalent in the industry, with web frameworks such as Node.js and Express making it simple to create and deploy complex, data-driven web applications. This course will prepare you to use such frameworks and show you how to integrate them with NoSQL databases such as MongoDB.
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                    How do you optimally encode a text file? How do you find shortest paths in a map? How do you design a communication network? How do you route data in a network? What are the limits of efficient computation? This course, part of the Computer Science Essentials for Software Development Professional Certificate program, is an introduction to design and analysis of algorithms, and answers along the way these and many other interesting computational questions. You will learn about algorithms that operate on common data structures, for instance sorting and searching; advanced design and analysis techniques such as dynamic programming and greedy algorithms; advanced graph algorithms such as minimum spanning trees and shortest paths; NP-completeness theory; and approximation algorithms. After completing this course you will be able to design efficient and correct algorithms using sophisticated data structures for complex computational tasks.