Get updates on Eligibility, Admission, Placements Fees Structure
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 4092 | yes | MIT Cambridge |
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
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
Who it is for
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)
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
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.
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.
The Collaborative Data Science for Healthcare online course is brought to you by edX courtesy of the Massachusetts Institute of Technology (MIT).
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.