This course distills for you expert knowledge and skills mastered by professionals in Health Big Data Science and Bioinformatics. You will learn exciting facts about the human body biology and chemistry, genetics, and medicine that will be intertwined with the science of Big Data and skills to harness the avalanche of data openly available at your fingertips and which we are just starting to make sense of. We’ll investigate the different steps required to master Big Data analytics on real datasets, including Next Generation Sequencing data, in a healthcare and biological context, from preparing data for analysis to completing the analysis, interpreting the results, visualizing them, and sharing the results.
Big Data, Genes, and Medicine
뉴욕주립대학교이 강좌에 대하여
최근 조회 43,826회
학습자 경력 결과
50%
가 이 강좌를 수료한 후 새로운 커리어를 시작함
43%
가 이 강좌를 통해 확실한 경력상 이점을 얻음
20%
가 급여 인상 또는 승진 성취
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 마감일
일정에 따라 마감일을 재설정합니다.
고급 단계
완료하는 데 약 23시간 필요
영어
자막: 영어
귀하가 습득할 기술
BioinformaticsData Clustering AlgorithmsBig DataR Programming
학습자 경력 결과
50%
가 이 강좌를 수료한 후 새로운 커리어를 시작함
43%
가 이 강좌를 통해 확실한 경력상 이점을 얻음
20%
가 급여 인상 또는 승진 성취
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 마감일
일정에 따라 마감일을 재설정합니다.
고급 단계
완료하는 데 약 23시간 필요
영어
자막: 영어
제공자:
뉴욕주립대학교
The State University of New York, with 64 unique institutions, is the largest comprehensive system of higher education in the United States. Educating nearly 468,000 students in more than 7,500 degree and certificate programs both on campus and online, SUNY has nearly 3 million alumni around the globe.
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 2시간 필요
Genes and Data
After this module, you will be able to
완료하는 데 2시간 필요
11개 동영상 (총 59분), 2 개의 읽기 자료, 6 개의 테스트
11개의 동영상
Introduction to Module1m
DNA and Genes9m
RNA and Proteins6m
Transcription Process4m
Transcription Animation1m
Translation Process5m
Translation Animation2m
Data, Variables, and Big Datasets6m
Working with cBioPortal - Genetic Data Analysis9m
Working with cBioPortal - Gene Networks9m
2개의 읽기 자료
Module 1 cBioPortal Data Analytics10m
Module 1 Resources10m
6개 연습문제
DNA, RNA, Genes, and Proteins4m
Transcription and Translation Processes6m
Data, Variables, and Big Datasets4m
Working with cBioPortal6m
Module 1 Quiz20m
Module 1 cBioPortal Data Analytics8m
완료하는 데 5시간 필요
Preparing Datasets for Analysis
After this module, you will be able to:
완료하는 데 5시간 필요
13개 동영상 (총 75분), 4 개의 읽기 자료, 8 개의 테스트
13개의 동영상
Datasets and Files10m
Data Sources11m
Importance of Data Preprocessing4m
Data Preprocessing Tasks2m
Replacing Missing Values3m
Data Normalization9m
Data Discretization5m
Feature Selection3m
Data Sampling2m
Principles of R6m
R Language1m
Jupyter Notebooks 1017m
4개의 읽기 자료
Jupyter Notebooks Essentials10m
Notebook Module 2 Tutorial10m
Module 2 R Data Preprocessing10m
Module 2 Resources10m
8개 연습문제
Datasets and Files4m
Data Preprocessing Tasks4m
Replacing Missing Values2m
Normalization and Discretization4m
Data Reduction4m
Working with R4m
Module 2 Quiz20m
Module 2 R Data Preprocessing10m
완료하는 데 4시간 필요
Finding Differentially Expressed Genes
After this module, you will be able to
완료하는 데 4시간 필요
9개 동영상 (총 53분), 4 개의 읽기 자료, 6 개의 테스트
9개의 동영상
Overview of Feature Selection Methods13m
Filter Methods4m
Wrapper Methods4m
Evaluation Schemes7m
Selecting Differentially Expressed Genes3m
Heatmaps6m
R Scripts for Feature Selection3m
Jupyter Notebooks 1017m
4개의 읽기 자료
Notebook Module 3 Tutorial10m
Jupyter Notebooks Essentials10m
Module 3 R Finding Differentially Expressed Genes10m
Module 3 Resources10m
6개 연습문제
Feature Selection Methods4m
Evaluation Schemes2m
Differentially Expressed Genes4m
Heatmaps4m
Module 3 Quiz16m
Module 3 R Finding Differentially Expressed Genes10m
완료하는 데 4시간 필요
Predicting Diseases from Genes
After this module, you will be able to
완료하는 데 4시간 필요
12개 동영상 (총 85분), 4 개의 읽기 자료, 10 개의 테스트
12개의 동영상
Overview of Classification and Prediction Methods8m
Classification Methods Based on Analogy12m
Classification Methods Based on Rules13m
Classification Methods Based on Neural Networks7m
Classification Methods Based on Statistics3m
Classification Methods Based on Probabilities7m
Prediction Methods4m
Evaluation Schemes13m
Prediction Workflow4m
R Scripts for Prediction1m
Jupyter Notebooks 1017m
4개의 읽기 자료
Jupyter Notebooks Essentials10m
Notebook Module 4 Tutorial10m
Module 4 R Predicting Diseases from Genes10m
Module 4 Resources10m
10개 연습문제
Overview4m
Classification with Analogy2m
Classification based on Rules2m
Classification with Neural Networks2m
Classification based on Statistics2m
Classification based on Probabilities2m
Prediction Models2m
Evaluation Schemes2m
Module 4 Quiz20m
Module 4 R Predicting Diseases from Genes10m
검토
BIG DATA, GENES, AND MEDICINE의 최상위 리뷰
AW 제공2020년 6월 11일
Very good for statistics information in regards to genes, medicine, and big data. I wish they would have spent more time on the R code and how to create it, but otherwise was a really good course.
BB 제공2020년 7월 1일
Very practical and easy to follow. The quizzes definitely help you retain the knowledge from the lectures. The hands-on with Jupyter Notebook was my favourite part of this course! Thank you!
MA 제공2019년 5월 9일
Really enjoying the way she is teaching. Very easy to learn and practice. I strongly believe when I will complete the course I will gain a remarkable skill on Big Data, Genes, and Medicine.
MP 제공2020년 5월 23일
A very informative course . I learn so many things from this course and this course has very good coverage in data and its analysis. thank you so much for providing this course
자주 묻는 질문
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