An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University.
This course is part of the Genomic Data Science Specialization
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Genomic Data Science SpecializationJohns Hopkins UniversityAbout this Course
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Learner Career Outcomes
40%
started a new career after completing these courses
38%
got a tangible career benefit from this course
17%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
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Start instantly and learn at your own schedule.
Course 7 of 8 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 9 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Skills you will gain
StatisticsData AnalysisR ProgrammingBiostatistics
Learner Career Outcomes
40%
started a new career after completing these courses
38%
got a tangible career benefit from this course
17%
got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Course 7 of 8 in the
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 9 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Offered by
Johns Hopkins University
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.
Syllabus - What you will learn from this course
3 hours to complete
Module 1
This course is structured to hit the key conceptual ideas of normalization, exploratory analysis, linear modeling, testing, and multiple testing that arise over and over in genomic studies.
3 hours to complete
21 videos (Total 129 min), 3 readings, 1 quiz
2 hours to complete
Module 2
This week we will cover preprocessing, linear modeling, and batch effects.
2 hours to complete
14 videos (Total 97 min)
2 hours to complete
Module 3
This week we will cover modeling non-continuous outcomes (like binary or count data), hypothesis testing, and multiple hypothesis testing.
2 hours to complete
15 videos (Total 86 min)
2 hours to complete
Module 4
In this week we will cover a lot of the general pipelines people use to analyze specific data types like RNA-seq, GWAS, ChIP-Seq, and DNA Methylation studies.
2 hours to complete
14 videos (Total 74 min), 1 reading, 1 quiz
Reviews
TOP REVIEWS FROM STATISTICS FOR GENOMIC DATA SCIENCE
by RHFeb 11, 2017
Overall, a very good course. Not without its flaws (inconsistent video audio levels), but I have walked away knowing far more about Genomic Data Science than I expected to.
by ZMJun 27, 2018
The professor is really enthusiasm, so I was really impreesed by him. And his teaching is brief, and I can learn key points through the lectures. Great course!
by NSFeb 18, 2019
sometimes termininology was used interchangeably, which can be confusing for a beginner but overall a good introduction to statistcs for genomic data analysis
by SFeb 18, 2018
Enjoyed it. One of better courses I have taken in Coursera. A good introduction to using statistics in Bioconductor with genomics data.
About the Genomic Data Science Specialization
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.
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