课程信息

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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.

Needless to say, when you master these high-demand skills, you will be well positioned to apply for or move to positions in biomedical data analytics and bioinformatics. No matter what your skill levels are in biomedical or technical areas, you will gain highly valuable new or sharpened skills that will make you stand-out as a professional and want to dive even deeper in biomedical Big Data. It is my hope that this course will spark your interest in the vast possibilities offered by publicly available Big Data to better understand, prevent, and treat diseases.

Learner Career Outcomes

50%

完成这些课程后已开始新的职业生涯

43%

通过此课程获得实实在在的工作福利

20%

加薪或升职

100% 在线

立即开始，按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

高级

完成时间大约为24 小时

建议：6 weeks of study, 3-5 hours per week...

英语（English）

字幕：英语（English）

您将获得的技能

BioinformaticsData Clustering AlgorithmsBig DataR Programming

Learner Career Outcomes

50%

完成这些课程后已开始新的职业生涯

43%

通过此课程获得实实在在的工作福利

20%

加薪或升职

100% 在线

立即开始，按照自己的计划学习。

可灵活调整截止日期

根据您的日程表重置截止日期。

高级

完成时间大约为24 小时

建议：6 weeks of study, 3-5 hours per week...

英语（English）

字幕：英语（English）

教学大纲 - 您将从这门课程中学到什么

周

1

周 1

完成时间为 2 小时

Genes and Data

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.

完成时间为 2 小时

11 个视频（总计 59 分钟）, 2 个阅读材料, 6 个测验

11 个视频

Introduction to the Course1分钟

Introduction to Module1分钟

DNA and Genes9分钟

RNA and Proteins6分钟

Transcription Process4分钟

Transcription Animation1分钟

Translation Process5分钟

Translation Animation2分钟

Data, Variables, and Big Datasets6分钟

Working with cBioPortal - Genetic Data Analysis9分钟

Working with cBioPortal - Gene Networks9分钟

2 个阅读材料

Module 1 cBioPortal Data Analytics10分钟

Module 1 Resources10分钟

6 个练习

DNA, RNA, Genes, and Proteins4分钟

Transcription and Translation Processes6分钟

Data, Variables, and Big Datasets4分钟

Working with cBioPortal6分钟

Module 1 Quiz20分钟

Module 1 cBioPortal Data Analytics8分钟

周

2

周 2

完成时间为 5 小时

Preparing Datasets for Analysis

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.

完成时间为 5 小时

13 个视频（总计 75 分钟）, 4 个阅读材料, 8 个测验

13 个视频

Introduction to Module4分钟

Datasets and Files10分钟

Data Sources11分钟

Importance of Data Preprocessing4分钟

Data Preprocessing Tasks2分钟

Replacing Missing Values3分钟

Data Normalization9分钟

Data Discretization5分钟

Feature Selection3分钟

Data Sampling2分钟

Principles of R6分钟

R Language1分钟

Jupyter Notebooks 1017分钟

4 个阅读材料

Jupyter Notebooks Essentials10分钟

Notebook Module 2 Tutorial10分钟

Module 2 R Data Preprocessing10分钟

Module 2 Resources10分钟

8 个练习

Datasets and Files4分钟

Data Preprocessing Tasks4分钟

Replacing Missing Values2分钟

Normalization and Discretization4分钟

Data Reduction4分钟

Working with R4分钟

Module 2 Quiz20分钟

Module 2 R Data Preprocessing10分钟

周

3

周 3

完成时间为 4 小时

Finding Differentially Expressed Genes

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.

完成时间为 4 小时

9 个视频（总计 53 分钟）, 4 个阅读材料, 6 个测验

9 个视频

Introduction to Module2分钟

Overview of Feature Selection Methods13分钟

Filter Methods4分钟

Wrapper Methods4分钟

Evaluation Schemes7分钟

Selecting Differentially Expressed Genes3分钟

Heatmaps6分钟

R Scripts for Feature Selection3分钟

Jupyter Notebooks 1017分钟

4 个阅读材料

Notebook Module 3 Tutorial10分钟

Jupyter Notebooks Essentials10分钟

Module 3 R Finding Differentially Expressed Genes10分钟

Module 3 Resources10分钟

6 个练习

Feature Selection Methods4分钟

Evaluation Schemes2分钟

Differentially Expressed Genes4分钟

Heatmaps4分钟

Module 3 Quiz16分钟

Module 3 R Finding Differentially Expressed Genes10分钟

周

4

周 4

完成时间为 4 小时

Predicting Diseases from Genes

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.

完成时间为 4 小时

12 个视频（总计 85 分钟）, 4 个阅读材料, 10 个测验

12 个视频

Introduction to Module9

Overview of Classification and Prediction Methods8分钟

Classification Methods Based on Analogy12分钟

Classification Methods Based on Rules13分钟

Classification Methods Based on Neural Networks7分钟

Classification Methods Based on Statistics3分钟

Classification Methods Based on Probabilities7分钟

Prediction Methods4分钟

Evaluation Schemes13分钟

Prediction Workflow4分钟

R Scripts for Prediction1分钟

Jupyter Notebooks 1017分钟

4 个阅读材料

Jupyter Notebooks Essentials10分钟

Notebook Module 4 Tutorial10分钟

Module 4 R Predicting Diseases from Genes10分钟

Module 4 Resources10分钟

10 个练习

Overview4分钟

Classification with Analogy2分钟

Classification based on Rules2分钟

Classification with Neural Networks2分钟

Classification based on Statistics2分钟

Classification based on Probabilities2分钟

Prediction Models2分钟

Evaluation Schemes2分钟

Module 4 Quiz20分钟

Module 4 R Predicting Diseases from Genes10分钟

周

5

周 5

完成时间为 4 小时

Determining Gene Alterations

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.

完成时间为 4 小时

9 个视频（总计 81 分钟）, 4 个阅读材料, 8 个测验

9 个视频

Introduction to Module1分钟

Overview of Gene Alterations16分钟

Genetic Mutations9分钟

Finding Genetic Mutations7分钟

Methylation8分钟

Copy Number Alterations10分钟

Genomic Alterations and Gene Expressions16分钟

R Scripts for Gene Alterations1分钟

Jupyter Notebooks 1017分钟

4 个阅读材料

Notebook Module 5 Tutorial10分钟

Jupyter Notebooks Essentials10分钟

Module 5 R Gene Alterations10分钟

Module 5 Resources10分钟

8 个练习

Gene Alterations4分钟

Gene Mutations6分钟

Methylation2分钟

Copy Number Alterations4分钟

Genomic Alterations and Gene Expressions4分钟

Module 5 Quiz (Temporary)20分钟

Module 5 Quiz20分钟

Module 5 R Gene Alterations10分钟

周

6

周 6

完成时间为 4 小时

Clustering and Pathway Analysis

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.

完成时间为 4 小时

12 个视频（总计 73 分钟）, 5 个阅读材料, 5 个测验

12 个视频

Introduction to Module2分钟

Overview of Clustering Methods7分钟

Similarity Assessment8分钟

Clustering with KMeans7分钟

Density Based Clustering4分钟

Hierarchical Clustering6分钟

Pathway Analysis12分钟

Pathway Discovery7分钟

Pathway Visualization6分钟

R Scripts for Clustering and Pathway Analysis1分钟

Jupyter Notebooks 1017分钟

Concluding Remarks1分钟

5 个阅读材料

Jupyter Notebooks Essentials10分钟

Notebook Module 6 Tutorial10分钟

Module 6 R Clustering and Pathways10分钟

Module 6 Resources10分钟

Acknowledgements10分钟

5 个练习

Clustering6分钟

Clustering Methods6分钟

Pathways4分钟

Module 6 Quiz20分钟

Module 6 R Clustering and Pathways10分钟

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Big Data, Genes, and Medicine