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Quick Facts

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

Course Overview

Traditionally, research has been viewed as a purely academic undertaking, especially in resource-limited healthcare systems. Not all countries can afford clinical trials. As such, the findings and results of studies conducted in the United States and other Western and developed countries are generalised. The Collaborative Data Science for Healthcare course shines a light on why there is a need for localised research.

The Collaborative Data Science for Healthcare programme aims to position research and data at the centre of all healthcare operations. It is an introduction and a survey of all the data science tools that are used in healthcare. The Collaborative Data Science for Healthcare syllabus includes numerous exercises and hands-on workshops to highlight the significance of a multi-disciplinary approach to data science in healthcare.

Ideally, clinicians and engineers/computer scientists should take the Collaborative Data Science for Healthcare course together, as a team. This Collaborative Data Science for Healthcare classes on data analysis is brought to you by members of the MIT Critical Data team and is a 12-week long free online course. This self-paced programme can be taken either in the paid mode or in the free audit mode. The paid mode will provide unlimited access to the course as well as a certificate of completion whereas the free audit mode will give access only for a limited duration.

The Highlights

Free Course
12-week course
Research project
English transcripts
2-3 hours per week
Hands-on workshops
Advanced level course
Instructor-led, scheduled course
Self-paced programme
Official, verified, shareable completion certificate

Programme Offerings

advanced level course
12-Week Programme
2-3 Hours Per Week
Free learning
Official Verified Completion Certificate Available
English Transcripts
Instructor-led learning
Course Schedule
Research Projects
Hands-on Workshops

Courses and Certificate Fees

Fees Informations	Certificate Availability	Certificate Providing Authority
INR 4078	yes	MIT Cambridge

Learners need not pay a fee to access the Collaborative Data Science for Healthcare online training. If they wish to, they can purchase an official, verified, and shareable completion certificate.

Collaborative Data Science for Healthcare online course fee structure

Training	Fees
Collaborative Data Science for Healthcare programme	NA.
Certification Fee	Rs. 4,078

Eligibility Criteria

Suppose someone from a healthcare/medicine background is taking the Collaborative Data Science for Healthcare online course individually, without teaming up with a computer scientist/engineer. In that case, they must have working knowledge and some experience in R, SQL or Python.

Candidates can choose to opt for a verified, shareable and official certification by edX. To avail this, they have to pay the fee specified by edX.

What you will learn

Machine learningData science knowledgeKnowledge of Artificial Intelligence

Candidates should have a thorough understanding of the following concepts after completing the Collaborative Data Science for Healthcare training programme:

Analysis of electronic health records
Principles of data science that apply to healthcare
Machine learning and Artificial Intelligence in healthcare

Who it is for

Computer scientist

The Collaborative Data Science for Healthcare online course is perfect for:

Frontline Clinicians
Public Health Practitioners
Computer Scientists/Engineers
Social Scientists

Those with a background in healthcare/medicine will find the programming aspect challenging, and those with experience in computer science/engineering will find the clinical aspects challenging. Therefore, edX recommends that clinicians and computer scientists/engineers take the Collaborative Data Science for Healthcare online course together, as a team.

Admission Details

Step 1: Click on the given link to access the Collaborative Data Science for Healthcare online course page on the edX website directly: https://www.edx.org/course/collaborative-data-science-for-healthcare.

Step 2: Keep scrolling till you find the ‘Enrol’ button and click on it to open the enrolment page.

Step 3: Create an account on edX using your Google, Facebook, Apple, or Microsoft account. If you already have an edX account, enter your credentials and log in.

Step 4: Fill in the requisite details, follow the on-screen instructions, and complete the application process.

Application Details

edX does not require candidates to fill out a dedicated application form when applying to the Collaborative Data Science for Healthcare online course. Interested candidates can log in to their edX account and start learning for free. If they do not have an account on edX, they can create one easily using their Google, Facebook, Apple, or Microsoft account.

The Syllabus

Welcome to HST.953x

1.01: What is Data Science, Incomplete
1.02: A Data Science Revolution In Healthcare, Incomplete
1.03: Secondary Analysis of Electronic Health Records, Incomplete
1.04: Challenges in Health Data Science

2.00: Introduction, Incomplete
2.01: Formulating the Research Question, Incomplete
2.02: Defining the Patient Cohort, Incomplete
2.03: Data Preparation, Incomplete
2.04: Data Pre-processing, Incomplete
2.05: Missing Data, Incomplete
2.06: Noise Versus Outliers, Incomplete
2.07: Exploratory Data Analysis, Incomplete
2.08: Linear Regression, Incomplete
2.09: Additional Data Analysis Methods, Incomplete
2.10: Sensitivity Analysis and Model Validation, Incomplete
2.11: Causal Inference

3.01 Workshop: Tools for Data Science, Incomplete
3.02 Workshop: Exploratory Data Analysis (EDA), Incomplete
3.03 Workshop: Regression Models, Incomplete
3.04 Workshop: Predictive Models, Incomplete
3.05 Workshop: Fairness and Bias

End-of-Course Quiz (10 Questions), Incomplete
Closing and Thanks

Instructors

MIT Cambridge Frequently Asked Questions (FAQ's)

1: If I am a clinician, can I take the Collaborative Data Science for Healthcare course by myself?

If you are a clinician, you can take the Collaborative Data Science for Healthcare certification course by yourself, provided that you have working knowledge and some experience in R, SQL, and Python

2: If I am a computer engineer, do I need to team up with a clinician to take this course?

Yes, as an engineer, you will have difficulty understanding the clinical concepts and terminology in the Collaborative Data Science for Healthcare programme, which is why you should team up with a clinician.

3: Are there any workshops in the programme?

Yes, there are several exercises and workshops in the Collaborative Data Science for Healthcare online course. There is even a research project for learners to follow along.

4: Which institution is offering the online course?

The Collaborative Data Science for Healthcare online course is brought to you by edX courtesy of the Massachusetts Institute of Technology (MIT).

5: Who can take the Collaborative Data Science for Healthcare online course?

Frontline Clinicians, Public Health Practitioners, Computer Scientists/Engineers, and Social Scientists from all over the world, except Cuba, Iran, and Crimea (Ukraine), can take the Collaborative Data Science for Healthcare online course.