This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from Johns Hopkins University.
이 강좌는 Genomic Data Science 전문 분야의 일부입니다.
Python for Genomic Data Science
제공자:
About this Course
최근 조회 64,943회
학습자 경력 결과
40%
이 강좌를 수료한 후 새로운 경력 시작하기
33%
이 강좌를 통해 확실한 경력상 이점 얻기
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 전문 분야의 8개 강좌 중 3번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
완료하는 데 약 15시간 필요
영어
자막: 영어
귀하가 습득할 기술
BioinformaticsBiopythonPython ProgrammingGenomics
학습자 경력 결과
40%
이 강좌를 수료한 후 새로운 경력 시작하기
33%
이 강좌를 통해 확실한 경력상 이점 얻기
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 전문 분야의 8개 강좌 중 3번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
완료하는 데 약 15시간 필요
영어
자막: 영어
제공자:
존스홉킨스대학교
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 2시간 필요
Week One
This week we will have an overview of Python and take the first steps towards programming.
완료하는 데 2시간 필요
5개 동영상 (총 58분), 3 readings, 2 quizzes
5개의 동영상
Lecture 2.1 - First Steps Toward Programming Part 110m
Lecture 2.2 - First Steps Toward Programming Part 215m
Lecture 2.3 - First Steps Toward Programming Part 3 (8:57)8m
Lecture 2.4 - First Steps Toward Programming Part 4 (9:58)9m
3개의 읽기 자료
Welcome10m
Pre-Course Survey10m
Syllabus10m
2개 연습문제
Lecture 1 Quiz6m
Lecture 2 Quiz24m
완료하는 데 1시간 필요
Week Two
In this module, we'll be taking a look at Data Structures and Ifs and Loops.
완료하는 데 1시간 필요
4개 동영상 (총 50분)
4개의 동영상
Lecture 3.2: Data Structures Part 2 (10:41)10m
Lecture 4.1: Ifs and Loops Part 1 (11:26)11m
Lecture 4.2: Ifs and Loops Part 2 (15:28)15m
2개 연습문제
Lecture 3 Quiz20m
Lecture 4 Quiz20m
완료하는 데 1시간 필요
Week Three
In this module, we have a long three-part lecture on Functions as well as a 10-minute look at Modules and Packages.
완료하는 데 1시간 필요
4개 동영상 (총 38분)
4개의 동영상
Lecture 5.2: Functions Part 2 (8:20)8m
Lecture 5.3: Functions Part 3 (13:24)13m
Lecture 6: Modules and Packages (10:32)10m
2개 연습문제
Lecture 5 Quiz20m
Lecture 6 Quiz12m
완료하는 데 2시간 필요
Week Four
In this module, we have another long three-part lecture, this time about Communicating with the Outside, as well as a final lecture about Biopython.
완료하는 데 2시간 필요
4개 동영상 (총 46분), 2 readings, 3 quizzes
4개의 동영상
Lecture 7.2: Communicating with the Outside Part 2 (7:38)7m
Lecture 7.3: Communicating with the Outside Part 3 (17:42)17m
Lecture 8: Biopython (13:32)13m
2개의 읽기 자료
Final Exam Instructions10m
Post Course Survey10m
3개 연습문제
Lecture 7 Quiz10m
Lecture 8 Quiz10m
Final Exam (Read Instructions First)20m
검토
4.3
PYTHON FOR GENOMIC DATA SCIENCE의 최상위 리뷰
MK 제공Dec 13, 2016
Started very easy, but became quite hard at the end. Nicely structured and conveyes everything that is needed. However, sometimes I missed why specific tools have been used and not others.
KR 제공Jul 16, 2018
A very good course for its length and the amount of time it requires. It improved my python skills and knowledge of Genomics. I'm more engaged in my pursuits than before taking the course.
JD 제공Oct 6, 2017
Easy to understand and very powerful examples. Not just it made me familiar with python, it also made it easy for me to teach to my students and inspire them to pursue python further.
DD 제공Jul 18, 2019
Compared to the lectures, the final exam was very difficult. It would be great if the professors provide more practical examples in the lectures similar to exam questions.
DK 제공May 10, 2018
I learned a lot. The final exam was more difficult than the course content, but I think it was critical for ensuring that I was able to apply the course content.
BG 제공Feb 2, 2018
You better know a lot about Python if you plan to pass this course!! Items covered in lecture are elementary. Items covered in exams/quiz's are Graduate Level!!!
AK 제공Feb 27, 2016
good course for python but you definitely need to have some background in programming to be able to pass. recommend python course by UMichigan here at Coursera.
AA 제공Apr 30, 2016
Great introduction to genomic data science using Python. The questions were challenging enough to make you work and wasn't too difficult that you get blocked.
Genomic Data Science 전문 분야 정보
With genomics sparks a revolution in medical discoveries, it becomes imperative to be able to better understand the genome, and be able to leverage the data and information from genomic datasets. Genomic Data Science is the field that applies statistics and data science to the genome.
This Specialization covers the concepts and tools to understand, analyze, and interpret data from next generation sequencing experiments. It teaches the most common tools used in genomic data science including how to use the command line, along with a variety of software implementation tools like Python, R, Bioconductor, and Galaxy.
This Specialization is designed to serve as both a standalone introduction to genomic data science or as a perfect compliment to a primary degree or postdoc in biology, molecular biology, or genetics, for scientists in these fields seeking to gain familiarity in data science and statistical tools to better interact with the data in their everyday work.
To audit Genomic Data Science courses for free, visit https://www.coursera.org/jhu, click the course, click Enroll, and select Audit. Please note that you will not receive a Certificate of Completion if you choose to Audit.
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.
이 전문 분야를 구독하면 무엇을 이용할 수 있나요?
강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.
환불 규정은 어떻게 되나요?
재정 지원을 받을 수 있나요?
궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.
