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.
제공자:
Genomic Data Science 특화 과정존스홉킨스대학교이 강좌에 대하여
최근 조회 86,288회
학습자 경력 결과
40%
가 이 강좌를 수료한 후 새로운 커리어를 시작함
33%
가 이 강좌를 통해 확실한 경력상 이점을 얻음
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 8개 강좌 중 3번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
완료하는 데 약 6시간 필요
영어
자막: 영어
귀하가 습득할 기술
BioinformaticsBiopythonPython ProgrammingGenomics
학습자 경력 결과
40%
가 이 강좌를 수료한 후 새로운 커리어를 시작함
33%
가 이 강좌를 통해 확실한 경력상 이점을 얻음
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
다음 특화 과정의 8개 강좌 중 3번째 강좌:
유동적 마감일
일정에 따라 마감일을 재설정합니다.
완료하는 데 약 6시간 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 개의 읽기 자료, 2 개의 테스트
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 개의 읽기 자료, 3 개의 테스트
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
PYTHON FOR GENOMIC DATA SCIENCE의 최상위 리뷰
AD 제공2020년 6월 14일
This course teaches you basics only, but when the questions are asked in the quiz they are no where related to what has been taught, and the level of difficulty of those questions is really high.
SM 제공2020년 4월 28일
The lectures were very good. However, the final exam was poor with unclear instructions on how to solve the questions. Also, the final exam questions and the lectures were not very related.
MK 제공2016년 12월 13일
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 제공2018년 7월 16일
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.
Genomic Data Science 특화 과정 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
When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
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