About this course: 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.
Who is this class for: This course is primarily aimed at health care professionals or assistants, and those with a BS/MA/MS in science or technology or equivalent professional experience. Minimum technical skills are a good understanding of using an Excel spreadsheet. Additional prerequisite knowledge in basic statistics would be preferred, however additional resources will be made available to learners to acquire this knowledge. I think that anyone interested in getting insights into how to harness Big Data to better understand, prevent, and treat diseases can take this course because the material can be applied at different levels of expertise.
Taught by: Isabelle Bichindaritz, Associate Professor
Computer Science
| Level | Advanced |
| Commitment | 6 weeks of study, 3-5 hours per week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
- Video: Introduction to the Course
- Video: Introduction to Module
- Video: DNA and Genes
- Video: RNA and Proteins
- Quiz pour s'exercer: DNA, RNA, Genes, and Proteins
- Video: Transcription Process
- Video: Transcription Animation
- Video: Translation Process
- Video: Translation Animation
- Quiz pour s'exercer: Transcription and Translation Processes
- Video: Data, Variables, and Big Datasets
- Quiz pour s'exercer: Data, Variables, and Big Datasets
- Video: Working with cBioPortal - Genetic Data Analysis
- Video: Working with cBioPortal - Gene Networks
- Quiz pour s'exercer: Working with cBioPortal
- Demande de discussion: Module 1 Discussion
- Lecture: Module 1 cBioPortal Data Analytics
- Lecture: Module 1 Resources
- Video: Introduction to Module
- Video: Datasets and Files
- Video: Data Sources
- Quiz pour s'exercer: Datasets and Files
- Video: Importance of Data Preprocessing
- Video: Data Preprocessing Tasks
- Quiz pour s'exercer: Data Preprocessing Tasks
- Video: Replacing Missing Values
- Quiz pour s'exercer: Replacing Missing Values
- Video: Data Normalization
- Video: Data Discretization
- Quiz pour s'exercer: Normalization and Discretization
- Video: Feature Selection
- Video: Data Sampling
- Quiz pour s'exercer: Data Reduction
- Video: Principles of R
- Video: R Language
- Quiz pour s'exercer: Working with R
- Bloc-notes: Module 2 Notebook
- Video: Jupyter Notebooks 101
- Lecture: Jupyter Notebooks Essentials
- Lecture: Notebook Module 2 Tutorial
- Demande de discussion: Module 2 Discussion
- Lecture: Module 2 R Data Preprocessing
- Bloc-notes: Module 2 Notebook
- Lecture: Module 2 Resources
- Video: Introduction to Module
- Video: Overview of Feature Selection Methods
- Video: Filter Methods
- Video: Wrapper Methods
- Quiz pour s'exercer: Feature Selection Methods
- Video: Evaluation Schemes
- Quiz pour s'exercer: Evaluation Schemes
- Video: Selecting Differentially Expressed Genes
- Quiz pour s'exercer: Differentially Expressed Genes
- Video: Heatmaps
- Quiz pour s'exercer: Heatmaps
- Video: R Scripts for Feature Selection
- Bloc-notes: Module 3 Notebook
- Lecture: Notebook Module 3 Tutorial
- Lecture: Jupyter Notebooks Essentials
- Video: Jupyter Notebooks 101
- Demande de discussion: Module 3 Discussion
- Lecture: Module 3 R Finding Differentially Expressed Genes
- Bloc-notes: Module 3 Notebook
- Lecture: Module 3 Resources
- Video: Introduction to Module
- Video: Overview of Classification and Prediction Methods
- Quiz pour s'exercer: Overview
- Video: Classification Methods Based on Analogy
- Quiz pour s'exercer: Classification with Analogy
- Video: Classification Methods Based on Rules
- Quiz pour s'exercer: Classification based on Rules
- Video: Classification Methods Based on Neural Networks
- Quiz pour s'exercer: Classification with Neural Networks
- Video: Classification Methods Based on Statistics
- Quiz pour s'exercer: Classification based on Statistics
- Video: Classification Methods Based on Probabilities
- Quiz pour s'exercer: Classification based on Probabilities
- Video: Prediction Methods
- Quiz pour s'exercer: Prediction Models
- Video: Evaluation Schemes
- Quiz pour s'exercer: Evaluation Schemes
- Video: Prediction Workflow
- Video: R Scripts for Prediction
- Bloc-notes: Module 4 Notebook
- Lecture: Jupyter Notebooks Essentials
- Video: Jupyter Notebooks 101
- Lecture: Notebook Module 4 Tutorial
- Demande de discussion: Module 4 Discussion
- Lecture: Module 4 R Predicting Diseases from Genes
- Lecture: Module 4 Resources
- Video: Introduction to Module
- Video: Overview of Gene Alterations
- Quiz pour s'exercer: Gene Alterations
- Video: Genetic Mutations
- Video: Finding Genetic Mutations
- Quiz pour s'exercer: Gene Mutations
- Video: Methylation
- Quiz pour s'exercer: Methylation
- Video: Copy Number Alterations
- Quiz pour s'exercer: Copy Number Alterations
- Video: Genomic Alterations and Gene Expressions
- Quiz pour s'exercer: Genomic Alterations and Gene Expressions
- Video: R Scripts for Gene Alterations
- Bloc-notes: Module 5 Notebook
- Video: Jupyter Notebooks 101
- Lecture: Notebook Module 5 Tutorial
- Lecture: Jupyter Notebooks Essentials
- Demande de discussion: Module 5 Discussion
- Quiz pour s'exercer: Module 5 Quiz (Temporary)
- Lecture: Module 5 R Gene Alterations
- Lecture: Module 5 Resources
- Video: Introduction to Module
- Video: Overview of Clustering Methods
- Video: Similarity Assessment
- Quiz pour s'exercer: Clustering
- Video: Clustering with KMeans
- Video: Density Based Clustering
- Video: Hierarchical Clustering
- Quiz pour s'exercer: Clustering Methods
- Video: Pathway Analysis
- Video: Pathway Discovery
- Video: Pathway Visualization
- Quiz pour s'exercer: Pathways
- Video: R Scripts for Clustering and Pathway Analysis
- Bloc-notes: Module 6 Notebook
- Video: Jupyter Notebooks 101
- Lecture: Jupyter Notebooks Essentials
- Lecture: Notebook Module 6 Tutorial
- Demande de discussion: Module 6 Discussion
- Lecture: Module 6 R Clustering and Pathways
- Lecture: Module 6 Resources
- Video: Concluding Remarks
- Lecture: Acknowledgements
Chaque cours fonctionne comme un manuel interactif en proposant des vidéos préenregistrées, des quiz et des projets.
Connectez-vous à des milliers d'autres étudiants et débattez sur des idées, discutez le contenu du cours et obtenez de l'aide pour en maîtriser les concepts.
Obtenez une reconnaissance officielle pour votre travail et partagez votre réussite avec vos amis, vos collègues et vos employeurs.
| Auditeur libre | Acheter le cours | |
|---|---|---|
| Accéder au contenu du cours | Available | Available |
| Accéder au contenu noté | Not available | Available |
| Recevoir une Note Finale | Not available | Available |
| Obtenir un Certificat de Cours partageable | Not available | Available |
This is an excellent course to learn about fundamental to intermediate level of "Big-data" in biomedical sciences and effective analysis. Very well designed and perfectly delivered by Prof. Bichindaritz. I would strongly recommend other genuine bioinformatics aspirants to enrol for this very course.
Thank you. :-)
Excellent introduction to how to run genetic data analytic applications on a big data infraestructure.
The theorical concepts related to data analytics were explained with highly professional quality; easy to understand for those with a data science backgroud. Also there were efective, efficient and acertive in the on the process of knowledge transference.
An outstanding course that exceed my expectations on regarding to data analytics theory and methods.
A good start. Congratulations.
The course has some minors mistakes that does not affect the essence of it.
Great course, it was exactly what I was missing to help me progress in my work analyzing genetic data. By studying the content, I gained in a short amount of time the new skills I needed to analyze genetic data. The course is very rich, and I enjoyed it very much. It is very visible that the professor is an expert in this field !
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Very good course for everyone new in the field of data science. Very good short lectures guiding you step by step to relevant skills and counclusions.