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Algorithms for DNA Sequencing

Genomic Data Science,

We will learn computational methods -- algorithms and data structures -- for analyzing DNA sequencing data. We will learn a little about DNA, genomics, and how DNA sequencing is used. We will use Python to implement key algorithms and data structures and to analyze real genomes and DNA sequencing datasets.
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Rating 4.7 based on 103 ratings
Length 5 weeks
Starts Aug 24 (5 weeks ago)
Cost $49
From Johns Hopkins University via Coursera
Instructors Ben Langmead, PhD, Jacob Pritt
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Data Analysis Algorithms

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What people are saying

homework assignments

Also, the "hints" to accomplish the homework assignments were definitely not well explained.

Some of the homework assignments were kind of hard though (and no help in the discussion forums).

The homework assignments are challenging, but created in such a way that the difficulty lies more in grappling with the concepts themselves, and less with debugging python code or whatever.

The homework assignments are challenging but not frustratingly so.

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other courses

The algorithms employed are much better explained than in some other bioinformatics courses on Coursera that deal with some similar topic (UCSD Specialisation, etc) as the course specifically deals with the algorithms rather than teaching bioinformatics in general (though I find the other courses quite good too).

I have taken six other courses in this JHU Genomics series on Coursera and many others in Data Science @ JHU, Cybersecurity @ the U of Maryland etc on Coursera.

genomic data science

Unlike some of the other courses in the Genomic Data Science Specialization, which have been shallow or poorly taught, this course is challenging (but not undoable) and the lectures are very well organized.

The assignments took me a lot of time because my only programming background is the 'Python for Genomic Data Science' course.

However, for somebody that only has the programming knowledge from Course 3 of the Genomic Data Science Specialization (Python for Genomic Data Science), that course, I believe, is too light for the new Python concepts taught in this course.

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for dna sequencing

Helpful material for DNA Sequencing and number crunching.Well taught, I suggest a background in Python to make things more enjoyable.

It would be very good to have another course for "Advanced algorithms for DNA sequencing" where strategies for dealing with the several complicators of actual genomic data are added on to the knowledge obtained in this course.

This is a good (albeit short) introduction to algorithms for DNA sequencing.

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taking this course

Excellent introduction to bioinformatics algorithms Really enjoyed taking this course.

Although you should get some python experience before taking this course.

Taking this course was a great experience: I learned a lot and enjoyed it a lot.

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lectures and practicals

Very impressed by the quality of the lectures and practicals.

The lectures and practicals are very easy to understand.

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Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Research Technologist, Laboratory Automation & Next-Generation Sequencing $37k

DNA Lab technician $45k

DNA Technician 1 $60k

Senior DNA Analyst $67k

Warehouse Sequencing Lead $70k

DNA Sequencer Manager $78k

Senior DNA Loan Analyst $92k

DNA Lab technician 2 $93k

DNA Sequencer 1 $95k

DNA/RNA Researcher $109k

DNA Lab technician Lead $116k

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Rating 4.7 based on 103 ratings
Length 5 weeks
Starts Aug 24 (5 weeks ago)
Cost $49
From Johns Hopkins University via Coursera
Instructors Ben Langmead, PhD, Jacob Pritt
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Science Data Analysis Algorithms

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