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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

Big Data, Genes, and Medicine Certification Programme brings carefully picked nuances of Bioinformatics and Health Big Data Science for enhancing the conceptual basics of candidates while providing them expertise and professionals skills in the concerning domain. This course will become an exciting experience for science enthusiasts who are fascinated by the mysteries of human body biology, its genetics and chemistry. These concepts will be related to medicine and Big Data to instil curiosity and consequent knowledge of Big Data in the learners.

Instructors will deal with important concepts related to Big Data analytics which will help them to gain a strong foothold over real datasets, not to forget Next Generation Sequencing data; all in a biological and healthcare context. The course covers a wide array of topics from preparing data for analysis, interpreting the results, visualising them, completing the analysis and ultimately sharing those results.

The curriculum is offered by the State University of New York, which has released this course as a part of its online training programme. Reputed as the largest comprehensive system of education in the US, it has proved itself to have a significant impact on the professional orientation of the learners.

The Highlights

Advanced level of training
Online and distance learning format
Subtitled video lectures in different languages
40 hours of course duration
Course offering by State University of New York (SUNY)

Programme Offerings

Online Format
practice assignments
additional readings
quizzes
video classrooms

Courses and Certificate Fees

Fees Informations	Certificate Availability	Certificate Providing Authority
INR 2381	yes	Coursera

Candidates willing to take up Big Data, Genes, and Medicine Certification and receive the certificate will have to pay the enrollment amount of Rs. 2,295.
No taxes are applicable on the course fee.

Fees	Amount in Rs.
	With certification	Without certification
Course Fee	2,381	Free
Total	2,381	Free

Eligibility Criteria

Certification Qualifying Details

Candidates pursuing the Big Data, Genes, and Medicine Certification Programme can purchase the certification after paying the fee for the same. It would be an online Certification and they shall receive the certificate on “My Accomplishments” tab only after completing the course in total and post staff and peer grading of the assignments submitted by them.

What you will learn

Knowledge of genetics

Big Data, Genes, and Medicine Certification shed light on many engaging concepts within the ambit of Health Informatics. The course is crafted to focus on the domain from an educational and professional point of view. After completion of the course, learners will gain information on-

How to locate and download files for data analysis that involves genes and medicine.
Evaluate the performance of feature selection methods.
Quantify genomic alterations.
Writing R scripts to classify and predict diseases from gene expressions.
Analyse and visualise biological pathways.

Who it is for

Bioinformatics Scientist

Big Data, Genes, and Medicine Certification Programme have been designed for various professional roles and designations in the health and Big Data science industry. Pursuing this course is particularly beneficial for-

Bioinformaticians
Biomedical data analysts
Big Data scientists
Science enthusiasts

Admission Details

All applicants have to follow a very direct and simple process for registering for Big Data, Genes, and Medicine Certification Programme course on Coursera. They are advised to follow this step-by-step guide for a hassle-free enrollment-

Step 1: Visit the course page. https://www.coursera.org/learn/data-genes-medicine

Step 2: Candidates will be able to see an “Enroll for Free” tab on the top of the webpage, clicking on which would display a dialogue box. Candidates have the option of choosing between the free version and paid version of the course.

Step 3: In order for further process to effectuate, candidates should be signed up on Coursera.

Step 4: If the candidate chooses the paid version, he will have to pay the required course fee there and then to get access to all the course material. On selecting the free version, candidates will get access to all the course material except quizzes. They will have to tap on “Start Learning” to begin learning.

The Syllabus

Videos

Introduction to Module
Introduction to the Course
Transcription Process
Transcription Animation
RNA and Proteins
Translation Process
DNA and Genes
Data, Variables, and Big Datasets
Translation Animation
Working with cBioPortal - Genetic Data Analysis

Readings

Module 1 cBioPortal Data Analytics
Module 1 Resources

Practice Exercises

DNA, RNA, Genes, and Proteins
Transcription and Translation Processes
Data, Variables, and Big Datasets
Working with cBioPortal
Module 1 Quiz
Module 1 cBioPortal Data Analytics

Videos

Introduction to Module
Datasets and Files
Data Sources
Importance of Data Preprocessing
Data Preprocessing Tasks
Replacing Missing Values
Data Normalization
Data Discretization
Feature Selection
Data Sampling
Principles of R
R Language
Jupyter Notebooks 101

Readings

Jupyter Notebooks Essentials
Notebook Module 2 Tutorial
Module 2 R Data Preprocessing
Module 2 Resources

Practice Exercises

Datasets and Files
Data Preprocessing Tasks
Replacing Missing Values
Normalization and Discretization
Data Reduction
Working with R
Module 2 Quiz
Module 2 R Data Preprocessing

Videos

Introduction to Module
Overview of Feature Selection Methods
Filter Methods
Wrapper Methods
Evaluation Schemes
Selecting Differentially Expressed Genes
Heatmaps
R Scripts for Feature Selection
Jupyter Notebooks 101

Readings

Notebook Module 3 Tutorial
Jupyter Notebooks Essentials
Module 3 R Finding Differentially Expressed Genes
Module 3 Resources

Practice Exercises

Feature Selection Methods
Evaluation Schemes
Differentially Expressed Genes
Heatmaps
Module 3 Quiz
Module 3 R Finding Differentially Expressed Genes

Videos

Introduction to Module
Overview of Classification and Prediction Methods
Classification Methods Based on Analogy
Classification Methods Based on Rules
Classification Methods Based on Neural Networks
Classification Methods Based on Statistics
Classification Methods Based on Probabilities
Prediction Methods
Evaluation Schemes
Prediction Workflow
R Scripts for Prediction
Jupyter Notebooks 101

Readings

Jupyter Notebooks Essentials
Notebook Module 4 Tutorial
Module 4 R Predicting Diseases from Genes
Module 4 Resources

Practice Exercises

Overview
Classification with Analogy
Classification based on Rules
Classification with Neural Networks
Classification based on Statistics
Classification based on Probabilities
Prediction Models
Evaluation Schemes
Module 4 Quiz
Module 4 R Predicting Diseases from Genes

Videos

Introduction to Module
Overview of Gene Alterations
Genetic Mutations
Finding Genetic Mutations
Methylation
Copy Number Alterations
Genomic Alterations and Gene Expressions
R Scripts for Gene Alterations
Jupyter Notebooks 101

Readings

Notebook Module 5 Tutorial
Jupyter Notebooks Essentials
Module 5 R Gene Alterations
Module 5 Resources

Practice Exercises

Gene Alterations
Gene Mutations
Methylation
Copy Number Alterations
Genomic Alterations and Gene Expressions
Module 5 Quiz (Temporary)
Module 5 Quiz
Module 5 R Gene Alterations

Videos

Introduction to Module
Overview of Clustering Methods
Similarity Assessment
Clustering with KMeans
Density Based Clustering
Hierarchical Clustering
Pathway Analysis
Pathway Discovery
Pathway Visualization
R Scripts for Clustering and Pathway Analysis
Jupyter Notebooks 101
Concluding Remarks

Readings

Jupyter Notebooks Essentials
Notebook Module 6 Tutorial
Module 6 R Clustering and Pathways
Module 6 Resources
Acknowledgements

Practice Exercises

Clustering
Clustering Methods
Pathways
Module 6 Quiz
Module 6 R Clustering and Pathways

Instructors

SUNY Frequently Asked Questions (FAQ's)

1: Is there any mobile application for accessing the course?

Coursera has a mobile application supported on both iOS and Android. For Android, candidates will have to ensure their OS version is Android 4.4 (Kit Kat) or higher.

2: What can be done to locate the missing work on Jupyter Notebook?

To recover work, candidates can-

Find their current notebook version by checking the top of the notebook window for the title
Click the Coursera logo in their notebook view
Find and click the name of their previous file

3: How are peer-reviewed assignments graded?

The following way is used for grading-

Firstly, the peer checks the assignment and attributes a grade to it.
Thereafter, the median score calculated for every assignment totals up to the final grade.
Lastly, all the final grades are summed up to calculate the total grade for a particular assignment.

4: Is there any age limit to access this course?

The learner’s age should be 13 years or older to take up this course on Coursera unless they belong to any country from the European Economic Area (EEA) where the limit differs.

5: Is there any accomodation on Coursera for visually impaired learners?

Most features on Coursera are compatible with screen readers so visually impaired learners can make use of the same while pursuing the course.