The State University of New York

Big Data, Genes, and Medicine

Taught in English

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33,996 already enrolled

Course

Gain insight into a topic and learn the fundamentals

4.2

(273 reviews)

Advanced level
Designed for those already in the industry
40 hours to complete
3 weeks at 13 hours a week
Flexible schedule
Learn at your own pace

Details to know

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Assessments

43 quizzes

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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 quizzes1 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 quizzes1 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 quizzes1 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 quizzes1 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 quizzes1 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 quizzes1 discussion prompt1 ungraded lab

Instructor

Instructor ratings
4.3 (61 ratings)
Isabelle Bichindaritz
The State University of New York
1 Course33,996 learners

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Recommended if you're interested in Health Informatics

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Showing 3 of 273

4.2

273 reviews

  • 5 stars

    54.74%

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    28.83%

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    8.39%

  • 2 stars

    2.55%

  • 1 star

    5.47%

SB
4

Reviewed on Jun 22, 2020

BJ
5

Reviewed on Feb 16, 2023

AA
5

Reviewed on May 9, 2019

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