This course will prepare you to complete all parts of the Clinical Data Science Specialization. In this course you will learn how clinical data are generated, the format of these data, and the ethical and legal restrictions on these data. You will also learn enough SQL and R programming skills to be able to complete the entire Specialization - even if you are a beginner programmer. While you are taking this course you will have access to an actual clinical data set and a free, online computational environment for data science hosted by our Industry Partner Google Cloud.
At the end of this course you will be prepared to embark on your clinical data science education journey, learning how to take data created by the healthcare system and improve the health of tomorrow's patients.
Этот курс входит в специализацию ''Специализация Clinical Data Science'
Introduction to Clinical Data Science
4.7
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14,814Чему вы научитесь
Describe how each type of clinical data are generated, specifically outlining who creates the data, when and why the data are generated.
Write SQL code to combine two or more tables using database joins.
Write R code to manipulate and tidy data including: selecting columns, filtering rows, and joining data sets.
Write markdown formatted text and combine with R code in RMarkdown documents.
Программа курса: что вы изучите
Неделя
11 ч. на завершение
Welcome to the Clinical Data Science Specialization
Learn what clinical data science is all about and get access to the free technology environment hosted by Google Cloud!
4 видео ((всего 16 мин.)), 5 материалов для самостоятельного изучения, 2 тестов
4 видео
Introduction to Clinical Data Science3мин
Clinical Data Regulations5мин
Introduction to the MIMIC-III Data Set4мин
5 материала для самостоятельного изучения
Introduction to Specialization Instructors5мин
Course Policies5мин
Accessing Course Data and Technology Platform15мин
Regulations and Health Privacy Resources10мин
MIMIC-III Resources and References10мин
2 практического упражнения
Week 1 Practice Quiz12мин
Week 1 Assessment16мин
Неделя
21 ч. на завершение
Introduction: Clinical Data
Clinical data are complex. Walk through the four-W's of clinical data to understand where they come from and what they look like.
7 видео ((всего 35 мин.)), 2 тестов
7 видео
Encounters4мин
Billing Data5мин
Laboratory Data7мин
Medication Data7мин
Clinical Observation Data1мин
Demographics, Social and Family History2мин
2 практического упражнения
Week 2 Practice Quiz8мин
Week 2 Assessment16мин
Неделя
33 ч. на завершение
Tools: SQL
Develop basic skills in SQL (Structured Query Language) and query the real clinical data set used in the Clinical Data Science Specialization.
5 видео ((всего 18 мин.)), 6 материалов для самостоятельного изучения, 2 тестов
5 видео
Querying Tables with SQL2мин
Joining Tables with SQL4мин
Aggregating Data with SQL4мин
Introduction to Google BigQuery3мин
6 материала для самостоятельного изучения
Introduction and Learning Objectives for Programming Examples and Exercises5мин
Guide to Google BigQuery Interface10мин
Querying and Aggregating Individual Tables with Google BigQuery 45мин
Querying and Joining Multiple Tables with Google BigQuery30мин
Joining Tables with SQL15мин
Note about the Assessment2мин
2 практического упражнения
Programming Exercises Practice Quiz24мин
Week 3 Assessment20мин
Неделя
42 ч. на завершение
Tools: R and the Tidyverse
Learn how to use the tidyverse to implement your Clinical Data Science Workflow in R.
2 видео ((всего 6 мин.)), 3 материалов для самостоятельного изучения, 2 тестов
3 материала для самостоятельного изучения
Working with RMarkdown Documents10мин
The Data Scientist's Workflow15мин
Note about the Assessment2мин
2 практического упражнения
Programming Exercises Practice Quiz22мин
Week 4 Assessment
4.7
Рецензии: 1750%
начал новую карьеру, пройдя эти курсы
33%
получил значимые преимущества в карьере благодаря этому курсу
Лучшие рецензии
Easy to understand, very professional and studying material is clear and relevant. I definitely recommend this course to jump into the clinical and healthcare data science world.
The material is presented very clearly, and exercises are easy to understand and complete but really test one's knowledge of the material.
Преподаватели
Laura K. Wiley, PhD
Assistant ProfessorDivision of Biomedical Informatics and Personalized Medicine, Anschutz Medical Campus
О Система университетов штата Колорадо
The University of Colorado is a recognized leader in higher education on the national and global stage. We collaborate to meet the diverse needs of our students and communities. We promote innovation, encourage discovery and support the extension of knowledge in ways unique to the state of Colorado and beyond.
О специализации ''Clinical Data Science'
Are you interested in how to use data generated by doctors, nurses, and the healthcare system to improve the care of future patients? If so, you may be a future clinical data scientist!
This specialization provides learners with hands on experience in use of electronic health records and informatics tools to perform clinical data science. This series of six courses is designed to augment learner’s existing skills in statistics and programming to provide examples of specific challenges, tools, and appropriate interpretations of clinical data.
By completing this specialization you will know how to: 1) understand electronic health record data types and structures, 2) deploy basic informatics methodologies on clinical data, 3) provide appropriate clinical and scientific interpretation of applied analyses, and 4) anticipate barriers in implementing informatics tools into complex clinical settings. You will demonstrate your mastery of these skills by completing practical application projects using real clinical data.
This specialization is supported by our industry partnership with Google Cloud. Thanks to this support, all learners will have access to a fully hosted online data science computational environment for free! Please note that you must have access to a Google account (i.e., gmail account) to access the clinical data and computational environment.
Часто задаваемые вопросы
Когда я получу доступ к лекциям и заданиям?
Зарегистрировавшись на сертификацию, вы получите доступ ко всем видео, тестам и заданиям по программированию (если они предусмотрены). Задания по взаимной оценке сокурсниками можно сдавать и проверять только после начала сессии. Если вы проходите курс без оплаты, некоторые задания могут быть недоступны.
Что я получу, оформив подписку на специализацию?
Записавшись на курс, вы получите доступ ко всем курсам в специализации, а также возможность получить сертификат о его прохождении. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.
Какие правила возврата средств?
Можно ли получить финансовую помощь?
I live in an area that restricts access to Google products. Will I be able to complete the specialization?
Unfortunately at this time we can only allow students who have access to Google services (e.g., a gmail account) to complete the specialization. This is because we give students access to real clinical data and our privacy protections only allow data sharing through the Google BigQuery environment.
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