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Coursera: Python for Genomic Data Science

 with  Mihaela Pertea and Steven Salzberg
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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.

12 Student
reviews
Cost Free Online Course (Audit)
Pace Upcoming
Subject Bioinformatics
Provider Coursera
Language English
Certificates Paid Certificate Available
Hours 3-5 hours a week
Calendar 4 weeks long
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12 reviews for Coursera's Python for Genomic Data Science

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4 out of 4 people found the following review useful
2 years ago
Brandt Pence completed this course, spending 3 hours a week on it and found the course difficulty to be medium.
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 commonly in bioinformatics due to its simple syntax and the wealth of packages Read More
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 commonly in bioinformatics due to its simple syntax and the wealth of packages (e.g. Biopython, NumPy) available for data processing and genomics. There's very little in the course material that will assist students in actually learning to code prior to the final exam, as most of the quiz questions simply ask students to determine which given lines of code will produce the desired output.

The final exam then throws students into the deep end. For those without significant Python coding experience or years of experience in another language, the final exam will be somewhere between extremely difficult and impossible. There is a serious loophole in the final exam that allows students to score highly without doing any coding, however. As with all the other classes in the JHU specializations, students are allowed 3 attempts at the exam, and the exam itself is multiple choice with 4 answers per question. Additionally, the instructors have coded more than 4 answers for each question, so incorrect answers cycle in and out of the potential answer bank between multiple tests. This means that students who take the test 3 times are often presented with a situation where only 1 or 2 of the 4 choices shows up on all 3 attempts, making it easy to determine which is the right answer if you keep your previous attempts open while taking the third exam and carefully note your previous wrong answers and the choices which appear in all 3 tests.

My minimal coding experience and careful use of Biopython was enough to allow me to to answer the first 3 of 10 questions on the exam, but I scored 5/10, 8/10, and finally 10/10 using the strategy above in my 3 tries.

Overall, I'm giving this course two stars, the same as the Galaxy course. There must be a better way to introduce students to these topics than what the instructors have done in these courses so far. There has been too much of a disconnect between assumed knowledge and expectations in these first two courses (I'm ignoring Intro to Genomic Technologies, which is another story altogether). This is true of the Data Science specialization to a certain extent as well, but the jump between lecture content and course project expectations is likely too wide for most students here, unless they come from a background where they happen to have a fair bit of training in whatever topic happens to be the focus of the course and/or final project.
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6 out of 6 people found the following review useful
2 years ago
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Anonymous completed this course.
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 reviewer above me is absolutely correct, you really do not learn enough Read More
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 reviewer above me is absolutely correct, you really do not learn enough about programming to complete the final project. This course should be geared towards individuals with beginner/intermediate experience with programming, and that way you can focus MUCH more on Python-based bioinformatics tools such as PyMol and BioPython. If you're attempting to learn bioinformatics without knowing programming, you're not gonna make it. Take basic programming courses BEFORE starting any bioinformatics coursework.
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2 out of 2 people found the following review useful
2 years ago
Anonymous partially completed this course.
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 pro Read More
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.
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2 out of 3 people found the following review useful
2 years ago
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Anonymous is taking this course right now.
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 pers Read More
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)
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4 out of 6 people found the following review useful
2 years ago
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Anonymous partially completed this course.
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.
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2 years ago
Juan Reza completed this course, spending 4 hours a week on it and found the course difficulty to be easy.
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 using Python in the Algorithms for DNA Sequencing course in this special Read More
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 using Python in the Algorithms for DNA Sequencing course in this specialization. Specifically, the Algorithms course uses Anaconda and its IDE, Notebook as used on a Mac or UNIX environment. There is a significant learning curve for Notebook in the Algorithms course which the instructors seem to be oblivious to because they are happily using a MAC. They state that you can do the work on a PC (or non-MAC unix) but they fail to provide the setup procedures which should have been provided in this (Python ) course.

I rated this course as suitable for Intermediate programmer because it assumes that you know how to install the IDE on any platform, convert platform-specific source formats (know that it is required), know how to use "Notebook". You can get through this course without those tools but you are left unprepared for the next course in this specialization that requires those skills.

The course does not convince me that Python is a suitable language for genomics work.

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a year ago
Chrys completed this course, spending 2 hours a week on it and found the course difficulty to be easy.
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.
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0 out of 2 people found the following review useful
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0 out of 1 people found the following review useful
2 years ago
Chema Cortés completed this course.
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2 years ago
Colin Khein completed this course.
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2 years ago
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Alex Ivanov dropped this course.
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0 out of 3 people found the following review useful
3 years ago
Mohammed Elfatih Awad Mohammed is taking this course right now.
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