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 forma parte de Programa Especializado - Genomic Data Science
Python for Genomic Data Science
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Acerca de este Curso
58,650 vistas recientes
Resultados profesionales del estudiante
40%
comenzó una nueva carrera después de completar estos cursos
33%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Habilidades que obtendrás
BioinformaticsBiopythonPython ProgrammingGenomics
Resultados profesionales del estudiante
40%
comenzó una nueva carrera después de completar estos cursos
33%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 3 de 8 en
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Aprox. 13 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
Programa - Qué aprenderás en este curso
2 horas para completar
Week One
This week we will have an overview of Python and take the first steps towards programming.
2 horas para completar
5 videos (Total 58 minutos), 3 lecturas, 2 cuestionarios
5 videos
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
3 lecturas
Welcome10m
Pre-Course Survey10m
Syllabus10m
2 ejercicios de práctica
Lecture 1 Quiz6m
Lecture 2 Quiz24m
1 hora para completar
Week Two
In this module, we'll be taking a look at Data Structures and Ifs and Loops.
1 hora para completar
4 videos (Total 50 minutos)
4 videos
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
2 ejercicios de práctica
Lecture 3 Quiz20m
Lecture 4 Quiz20m
1 hora para completar
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 completar
4 videos (Total 38 minutos)
4 videos
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
2 ejercicios de práctica
Lecture 5 Quiz20m
Lecture 6 Quiz12m
2 horas para completar
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 completar
4 videos (Total 46 minutos), 2 lecturas, 3 cuestionarios
4 videos
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
2 lecturas
Final Exam Instructions10m
Post Course Survey10m
3 ejercicios de práctica
Lecture 7 Quiz10m
Lecture 8 Quiz10m
Final Exam (Read Instructions First)20m
Revisiones
Principales revisiones sobre PYTHON FOR GENOMIC DATA SCIENCE
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 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 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 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.
por GKOct 12, 2018
I learned a lot from this course, being new to coding. The content is tweaked towards bioinformatic problems and requires a good grasp of the topic to pass.
por AMApr 1, 2020
A few more simple practical assignments would be beneficial. I had no background of coding and needed more basics before I could grasp the concepts fully.
por CKJul 10, 2016
A great medium to learn python via, I'm not a biologist, but that is no barrier, and the backdrop is a great way to learn to play about with Python.
por PLJul 1, 2016
This course was in line with my expectations. Sometimes exercises were a bit out of context. I would have probably dedicated more time to Biopython.
Acerca de Universidad 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.
Acerca de Programa especializado Genomic Data Science
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.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
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