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.
Este curso faz parte do Programa de cursos integrados Análise de Dados GenômicosAnálise Genômica
Python para Análise de Dados Genômicos
oferecido por
Informações sobre o curso
62,530 visualizações recentes
Resultados de carreira do aprendiz
40%
comecei uma nova carreira após concluir estes cursos
33%
consegui um benefício significativo de carreira com este curso
Habilidades que você terá
BioinformaticsBiopythonPython ProgrammingGenomics
Resultados de carreira do aprendiz
40%
comecei uma nova carreira após concluir estes cursos
33%
consegui um benefício significativo de carreira com este curso
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Aprox. 6 horas para completar
Inglês
Legendas: Inglês
oferecido por
Universidade Johns Hopkins
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.
Programa - O que você aprenderá com este curso
2 horas para concluir
Week One
This week we will have an overview of Python and take the first steps towards programming.
2 horas para concluir
5 vídeos (Total 58 mín.), 3 leituras, 2 testes
5 videos
Lecture 2.1 - First Steps Toward Programming Part 110min
Lecture 2.2 - First Steps Toward Programming Part 215min
Lecture 2.3 - First Steps Toward Programming Part 3 (8:57)8min
Lecture 2.4 - First Steps Toward Programming Part 4 (9:58)9min
3 leituras
Welcome10min
Pre-Course Survey10min
Syllabus10min
2 exercícios práticos
Lecture 1 Quiz6min
Lecture 2 Quiz24min
1 hora para concluir
Week Two
In this module, we'll be taking a look at Data Structures and Ifs and Loops.
1 hora para concluir
4 vídeos (Total 50 mín.)
4 videos
Lecture 3.2: Data Structures Part 2 (10:41)10min
Lecture 4.1: Ifs and Loops Part 1 (11:26)11min
Lecture 4.2: Ifs and Loops Part 2 (15:28)15min
2 exercícios práticos
Lecture 3 Quiz20min
Lecture 4 Quiz20min
1 hora para concluir
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.
1 hora para concluir
4 vídeos (Total 38 mín.)
4 videos
Lecture 5.2: Functions Part 2 (8:20)8min
Lecture 5.3: Functions Part 3 (13:24)13min
Lecture 6: Modules and Packages (10:32)10min
2 exercícios práticos
Lecture 5 Quiz20min
Lecture 6 Quiz12min
2 horas para concluir
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.
2 horas para concluir
4 vídeos (Total 46 mín.), 2 leituras, 3 testes
4 videos
Lecture 7.2: Communicating with the Outside Part 2 (7:38)7min
Lecture 7.3: Communicating with the Outside Part 3 (17:42)17min
Lecture 8: Biopython (13:32)13min
2 leituras
Final Exam Instructions10min
Post Course Survey10min
3 exercícios práticos
Lecture 7 Quiz10min
Lecture 8 Quiz10min
Final Exam (Read Instructions First)20min
Avaliações
Principais avaliações do PYTHON PARA ANÁLISE DE DADOS GENÔMICOS
por KRJul 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.
por MKDec 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.
por JDOct 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.
por DDJul 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.
por BGFeb 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!!!
por DKMay 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.
por AKFeb 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.
por AAApr 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.
Sobre Programa de cursos integrados Análise de Dados GenômicosAnálise Genômica
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.
Perguntas Frequentes – FAQ
Quando terei acesso às palestras e às tarefas?
Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.
O que recebo ao me inscrever nesta Especialização?
Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.
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