John Hopkins University - Genomic Data Science Specialization
- Offered byCoursera
Genomic Data Science Specialization at Coursera Overview
Duration | 10 months |
Start from | Start Now |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Intermediate |
Official Website | Go to Website  |
Credential | Certificate |
Genomic Data Science Specialization at Coursera Highlights
- Next generation sequencing experiments
- Genomic technologies
- DNA, RNA and epigenetic patterns
- Genome analysis
Genomic Data Science Specialization at Coursera Course details
- This Specialization by Johns Hopkins University covers the concepts and tools to understand, analyze, and interpret data from next generation sequencing experiments. It teaches the most common tools used in genomic data science including how to use the command line, along with a variety of software implementation tools like Python, R, Bioconductor, and Galaxy.
- This Specialization is designed to serve as both a standalone introduction to genomic data science or as a perfect compliment to a primary degree or postdoc in biology, molecular biology, or genetics, for scientists in these fields seeking to gain familiarity in data science and statistical tools to better interact with the data in their everyday work.
Genomic Data Science Specialization at Coursera Curriculum
Introduction to Genomic Technologies
This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it. We'll introduce the Central Dogma of Molecular Biology and cover how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You'll also get an introduction to the key concepts in computing and data science that you'll need to understand how data from next-generation sequencing experiments are generated and analyzed.
Genomic Data Science with Galaxy
Learn to use the tools that are available from the Galaxy Project. This is the second course in the Genomic Big Data Science Specialization.
Python for Genomic Data Science
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.
Algorithms for DNA Sequencing
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.
Command Line Tools for Genomic Data Science
Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data. This is the fourth course in the Genomic Big Data Science Specialization from Johns Hopkins University.
Bioconductor for Genomic Data Science
Learn to use tools from the Bioconductor project to perform analysis of genomic data. This is the fifth course in the Genomic Big Data Specialization from Johns Hopkins University.
Statistics for Genomic Data Science
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.
Genomic Data Science Capstone
Genomic Data Science Specialization at Coursera Entry Requirements
- Some related experience required.
- Not mentioned
Genomic Data Science Specialization at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Student Forum
Anything you would want to ask experts?