This course distills for you expert knowledge and skills mastered by professionals in Health Big Data Science and Bioinformatics. You will learn exciting facts about the human body biology and chemistry, genetics, and medicine that will be intertwined with the science of Big Data and skills to harness the avalanche of data openly available at your fingertips and which we are just starting to make sense of. We’ll investigate the different steps required to master Big Data analytics on real datasets, including Next Generation Sequencing data, in a healthcare and biological context, from preparing data for analysis to completing the analysis, interpreting the results, visualizing them, and sharing the results.
Big Data, Genes, and Medicine
Gain insight into a topic and learn the fundamentals.
4.3
(284 reviews)
Advanced level
Designed for those already in the industry
Flexible schedule
4 weeks at 10 hours a week
Learn at your own pace
90%
Most learners liked this course
Skills you'll gain
Details to know
Shareable certificate
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Assessments
43 assignments
Taught in English
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There are 6 modules in this course
After this module, you will be able to 1. Locate and download files for data analysis involving genes and medicine. 2. Open files and preprocess data using R language. 3. Write R scripts to replace missing values, normalize data, discretize data, and sample data.
What's included
11 videos2 readings6 assignments1 discussion prompt
After this module, you will be able to: 1. Locate and download files for data analysis involving genes and medicine. 2. Open files and preprocess data using R language. 3. Write R scripts to replace missing values, normalize data, discretize data, and sample data.
What's included
13 videos4 readings8 assignments1 discussion prompt2 ungraded labs
After this module, you will be able to 1. Select features from highly dimensional datasets. 2. Evaluate the performance of feature selection methods. 3. Write R scripts to select features from datasets involving gene expressions.
What's included
9 videos4 readings6 assignments1 discussion prompt2 ungraded labs
After this module, you will be able to 1. Build classification and prediction models. 2. Evaluate the performance of classification and prediction methods. 3. Write R scripts to classify and predict diseases from gene expressions.
What's included
12 videos4 readings10 assignments1 discussion prompt1 ungraded lab
After this module, you will be able to 1. List different types of gene alterations. 2. Compare and contrast methods for detecting gene mutations. 3. Compare and contrast methods for detecting methylation. 4. Compare and contrast methods for detecting copy number variations. 5. Quantify genomic alterations. 6. Connect genomic alterations to differential expression of genes. 7. Write programs in R for determining gene alterations and their relationship with gene expression.
What's included
9 videos4 readings8 assignments1 discussion prompt1 ungraded lab
After this module, you will be able to 1. Find clusters in biomedical data involving genes.2. Analyze and visualize biological pathways. 3. Write R scripts for clustering and for pathway analysis.
What's included
12 videos5 readings5 assignments1 discussion prompt1 ungraded lab
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Instructor
Instructor ratings
4.3 (64 ratings)
Offered by
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Status: Free TrialUniversity of California San Diego
Status: Free TrialUniversity of Colorado System
Status: Free TrialUniversity of Colorado System
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4.3
284 reviews
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Showing 3 of 284
BJ
5
Reviewed on Feb 16, 2023
I learned a lot, all thanks to SUNY and coursera for gradually making my dream a reality.
AE
4
Reviewed on Jun 15, 2018
I feel like I wanted to have practice with the material that was covered in the lecture
VC
4
Reviewed on Aug 27, 2018
Apart form minor issues in the assessments, I really enjoyed this course as it was presented clearly and concise by professor Isabelle Bichindaritz
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