Learning Outcomes
How to bridge diverse genomic assay and annotation structures to data analysis and research presentations via innovative approaches to computing.
Professional Certificate Series
Data Analysis for Genomics
Learn advanced techniques to analyze genomic data
- 3 Courses
- 3 Months
- Earn Your Certificate
What You'll Learn
Advances in genomics have triggered fundamental changes in medicine and research.
Genomic datasets are driving the next generation of discovery and treatment, and this series will enable you to analyze and interpret data generated by modern genomics technology. Using open-source software, including R and Bioconductor, you will acquire skills to analyze and interpret genomic data. These courses are perfect for those who seek advanced training in high-throughput technology data. Problem sets will require coding in the R language to ensure mastery of key concepts. In the final course, you’ll investigate data analysis for several experimental protocols in genomics. Enroll now to unlock the wealth of opportunities in modern genomics.
Learn MoreLearning Outcomes
How to structure, annotate, normalize, and interpret genome-scale assays.
Learning Outcomes
How to analyze data from several experimental protocols, using open-source software, including R and Bioconductor.
3 Courses
Beyond our premium learning paths you can still earn certificates
Introduction to Bioconductor
2-4 hours per week
Advanced Bioconductor
2-4 hours a week
Case Studies in Functional Genomics
2-4 hours a week
Learn from the best in the industry
Meet your instructors
Michael Love
Assistant Professor, UNC Gillings School of Global Public Health
Rafael Irizarry
Professor of Biostatistics, Harvard T.H. Chan School of Public Health
Vincent Carey
Professor of Medicine, Harvard Medical School
Industry Insights
32% of full-time data scientists started learning machine learning or data science through a MOOC, while 27% were self-taught. (source: Kaggle, 2017)
R is listed as a required skill in 64% of data science job postings and was Glassdoor’s Best Job in America in 2016 and 2017. (source: Glassdoor)
Data Scientists are few in number and high in demand. (source: TechRepublic)
Companies are leveraging the power of data analysis to drive innovation. Google data analysts use R to track trends in ad pricing and illuminate patterns in search data. Pfizer created customized packages for R so scientists can manipulate their own data.