Implementation ScienceClinical Text MiningR ProgrammingComputational PhenotypingData Quality Assessment
Clinical Data Science 특화 과정
Launch your career in Clinical Data Science. A six-course introduction to using clinical data to improve the care of tomorrow's patients.
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Clinical Data Science 특화 과정콜로라도 대학교배울 내용
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.
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이 전문 분야 정보
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.
응용 학습 프로젝트
Each course in the specialization culminates in a final project that is a practical application of the tools and technique you learned throughout the course. In these projects you will apply your skills to a real clinical data set using the free, fully hosted online data science environment provided by our industry partner, Google Cloud.
학습자 경력 결과
20%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
25%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
중급 단계
Some programming experience and an interest in Clinical Data Science are required.
완료하는 데 약 7개월이 걸립니다
권장 학습 속도: 주 2시간
영어
자막: 영어, 프랑스어, 포르투갈어 (유럽), 러시아어, 스페인어
학습자 경력 결과
20%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
25%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
중급 단계
Some programming experience and an interest in Clinical Data Science are required.
완료하는 데 약 7개월이 걸립니다
권장 학습 속도: 주 2시간
영어
자막: 영어, 프랑스어, 포르투갈어 (유럽), 러시아어, 스페인어
이 전문 분야에는 6개의 강좌가 있습니다.
Introduction to Clinical Data Science
271개의 평가
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.
Clinical Data Models and Data Quality Assessments
51개의 평가
This course aims to teach the concepts of clinical data models and common data models. Upon completion of this course, learners will be able to interpret and evaluate data model designs using Entity-Relationship Diagrams (ERDs), differentiate between data models and articulate how each are used to support clinical care and data science, and create SQL statements in Google BigQuery to query the MIMIC3 clinical data model and the OMOP common data model.
Identifying Patient Populations
29개의 평가
This course teaches you the fundamentals of computational phenotyping, a biomedical informatics method for identifying patient populations. In this course you will learn how different clinical data types perform when trying to identify patients with a particular disease or trait. You will also learn how to program different data manipulations and combinations to increase the complexity and improve the performance of your algorithms. Finally, you will have a chance to put your skills to the test with a real-world practical application where you develop a computational phenotyping algorithm to identify patients who have hypertension. You will complete this work using a real clinical data set while using a free, online computational environment for data science hosted by our Industry Partner Google Cloud.
Clinical Natural Language Processing
17개의 평가
This course teaches you the fundamentals of clinical natural language processing (NLP). In this course you will learn the basic linguistic principals underlying NLP, as well as how to write regular expressions and handle text data in R. You will also learn practical techniques for text processing to be able to extract information from clinical notes. Finally, you will have a chance to put your skills to the test with a real-world practical application where you develop text processing algorithms to identify diabetic complications from clinical notes. You will complete this work using a free, online computational environment for data science hosted by our Industry Partner Google Cloud.
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콜로라도 대학교
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.
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전문 분야를 완료하면 대학 학점을 받을 수 있나요?
Can I just enroll in a single course?
하나의 강좌에만 등록할 수 있나요?
Can I take the course for free?
해당 강좌를 무료로 수강할 수 있나요?
이 강좌는 100% 온라인으로 진행되나요? 직접 참석해야 하는 수업이 있나요?
How long does it take to complete the Specialization?
전문 분야를 완료하는 데 얼마나 걸리나요?
Do I need to take the courses in a specific order?
Will I earn university credit for completing the Specialization?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.
