Adopting digital health records and sharing its data is a critical step forward. In order to foster better collaboration across patient healthcare providers, cutting edge tools and systems must be used to improve the quality of patient care. This course will look at academic and industry research and developments as it pertains to health informatics. You’ll learn how aggregated data can be used to understand public health issues and how it impacts your ability to treat disease. In addition, the course will also cover how digital data is driving predictive analytics to improve diagnosis and treatment, while effectively running hospital and health systems.
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As the exchange of health records and other clinical systems used in patient care become increasingly digital, the focus turns to how this health information can be communicated and shared throughout a patient’s health journey. While often a challenge, adopting health data standards in a comprehensive and seamless manner is key to enabling interoperability. In this course, you’ll discover how data and data sharing (interoperability) standards are interconnected to help achieve a cohesive health system across the entire organization and between electronic health record systems.
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The field of health informatics emphasis the management and use of patient healthcare information. In this course, you’ll gain a brief overview of its history and capabilities, as well as an understanding of its slow adoption within organizations. You’ll be introduced to the Fast Healthcare Interoperability (FHIR) standard and concept of a Learning Healthcare System. Class discussions will focus on alternate care models, electronic medical records, patient-facing informatics tools and approaches, and the technical and policy issues surrounding healthcare data sharing. Interviews and activities will illustrate learning objectives and provide insight into real world uses of health informatics across organizations.
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Businesses, consumers, and societies leave behind massive amounts of data as a by-product of their activities. Leading-edge companies in every industry are using analytics to replace intuition and guesswork in their decision making. As a result, managers are collecting and analyzing enormous data sets to discover new patterns and insights and running controlled experiments to test hypotheses. This course, part of the Analytics: Essential Tools and Methods MicroMasters program, prepares you to understand data and business analytics and become a leader in these areas in business organizations. It will illustrate the processes of analytics by allowing you to apply business analytics algorithms and methodologies to real- world business datasets from finance, marketing, and operations. The use of real-world examples and cases places business analytics techniques in context and teaches you how to avoid the common pitfalls, emphasizing the importance of applying proper business analytics techniques.
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In the 21st century, there are millions of innovators but few authentic innovation leaders able to inspire and guide innovators and their teams to create breakthrough products with their innovative ideas. In this original course, Innovation Leadership, you'll learn how to become an innovation leader. The essential elements of knowing yourself and your unique leadership gifts, your motivations, and the purpose of your leadership will be covered, along with personal stories of exceptional innovation leaders, concepts, exercises, tools and practical tips to help you become an exceptional innovation leader. Innovation Leadership is organized to focus on three modules, each including videos describing essential elements of innovation leaders, illustrating them with personal examples from innovation leaders, readings from Discover Your True North, illustrative charts, exercises, reflection essays, and discussion topics.
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This course is your hands-on introduction to programming techniques relevant to data analysis and machine learning. Most of the programming exercises will be based on Python and SQL.
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This course picks up with an overview of basic thermodynamics and kinetics as they pertain to the processing of crystalline materials. The first module deals with phase diagrams -- charts that tell us how a material will behave given a certain set of variables such as temperature, pressure, and composition. You will learn how to interpret common and complex phase diagrams and how to extract useful information from them.
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Analytical models are key to understanding data, generating predictions, and making business decisions. Without models, it is nearly impossible to gain insights from data. In modeling, it’s essential to understand how to choose the right data sets, algorithms, techniques, and formats to solve a particular business problem. In this course, part of the Analytics: Essential Tools and Methods MicroMasters program, you’ll gain an intuitive understanding of fundamental models and methods of analytics and practice how to implement them using common industry tools, such as R. You’ll learn about analytics modeling and how to choose the right approach from among the wide range of options in your toolbox.
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Looking to gain a solid understanding of what a supply chain is all about? This course provides a great introduction to the integrated supply chain model. You will have the chance to leverage discussions, videos, and quizzes to expand your foundational knowledge on the subject and find out about career opportunities in the field. The course also presents emerging and futuristic trends in supply chain.
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A direct current (DC) source is one that is constant. In this course, you will learn how to analyze circuits that have DC or voltage sources, including circuits with resistors, capacitors, and inductors. Some practical applications in sensors will be demonstrated as well.
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