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Johns Hopkins University

Python for Genomic Data Science

Johns Hopkins University via Coursera

Overview

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.

Syllabus

  • Week One
    • This week we will have an overview of Python and take the first steps towards programming.
  • Week Two
    • In this module, we'll be taking a look at Data Structures and Ifs and Loops.
  • 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.
  • 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.

Taught by

Mihaela Pertea and Steven Salzberg

Reviews

2.9 rating, based on 15 Class Central reviews

4.3 rating at Coursera based on 1682 ratings

Start your review of Python for Genomic Data Science

  • Brandt Pence
    This is the third course in the Genomic Data Science specialization. I have mixed feelings about this course. Much of the lecture material and the quizzes are devoted to introducing students to the Python programming language. Python is used commonl…
  • Anonymous
    Good course for learning (very) basic programming skills in Python, but horrible as a bioinformatics course. I think it was a mistake to gear it towards individuals with absolutely no programming experience, and them make it only 4 weeks long. The r…
  • this course is very basic. I've known python language before, so it takes me one day to finish the course completely
  • Juan Reza
    As a seasoned Java programmer learning the basics of Python taught by this course was very easy. However, the course has very little useful material on genomics. The most important failure of the course is that it does not prepare the student for u…
  • Reviewers thank you for sharing your thoughts.
    As a first course to learning Python and hoping to learn some bioinformatics application, this course would not be the best choice for absolute beginners. Simply reading and completing multiple choice questions will not equip you with the ability to complete the final project. You learn by practicing to program and the structure of the course is not conducive to best practices in computer science. It was totally discouraging for someone new like me. Appreciate the learning materials though.
  • Anonymous
    This course hurriedly skims through the topics.The quiz material has not been checked so the quizzes often do not have correct choices. Like other reviewers have mentioned above, this course cannot be a standalone for both introducing and doing bioinformatics with python in a span of 4 weeks. I am also going for a personal rant here, sorry guys: Dejan(one of the community TAs is very rude,unhelpful)
  • Profile image for Chrys
    Chrys
    This course is quite easy and will give you an insight into the very basics of python. As a beginner course on its own I would rate it higher because of the good videos and good instructors but since it is supposed to prepare you for other python courses in the specialisation I can not. It is to rudimentary to prepare you and you will have a hard time if you don't have prior expierence.
  • Anonymous
    PLEASE don't pay for this abomination. Better yet, don't even take it. There are good courses on Python both on Coursera and Udacity. This one does not help, and the final project is impossible to complete if you are new to Python.
  • Profile image for NARENDRA TEJA
    NARENDRA TEJA
    best quality information provided thank you and easy to handle the platform and easy to understand the class well
  • Profile image for Natthawut Max Adulyanukosol
    Natthawut Max Adulyanukosol
  • Profile image for Alex Ivanov
    Alex Ivanov
  • Pankaj Dhungana
    This is a nice course to begin Python for Genetics/Biology Student. Though it can be equally fascinating for anyone who loves the intersection between biology, computer science and.....

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