This video series is geared towards all the health professionals who want to have an understanding of data analytics. The aim is to alleviate the fear of numbers and to make you self-sufficient for your own research projects. This course comprises of four modules:
1. A dummy’s guide to analytics and statistics (Exp in SPSS)
2. R for Doctors
3. A to Z of Approaching an analytics project
4. Capstone project: Practical example of a full project on R
Each module is further structured as:
Module 1: A dummy’s guide to analytics
1. Core statistical concepts
a. Probability theory
b. Data / variable types and distributions
c. Measures of central tendencies and spread
2. Basic Tests (Exp in SPSS)
a. T-Tests (paired and unpaired)
b. Some Fancy tests (Mann-Whitney U & Wilcoxon signed-rank test)
c. Chi-square test
3. Regression – You beauty (Exp in SPSS)
a. Basic concepts and types
b. Assumptions and data preparation
c. Interpreting the results
4. A glimpse at advanced analytics
a. Nonlinear modeling (introduction)
b. Modern machine learning techniques (introduction)
Module 2: R for Doctors
1. Introduction to R
a. What is R and why
b. Installation
c. Getting started
2. R-Studio GUI and flow
a. The graphic user interface of R-Studio
b. Using basic commands
c. Simple troubleshooting and getting help
3. R Language Basics
a. The syntax – Object-oriented language
b. Data types in Medical perspective
c. Use of functions and constructs (basics)
4. Simple statistics and graphs with R
a. Examples of t-tests and chi-square test
b. Making beautiful graphs for real-life medical data Module
3: A-Z of an Analytics Project
1. Data analytics life cycle
a. What is an analytics lifecycle
b. Why need a structure in work
c. The 6 steps of approaching any project
2. The 6 steps explained
a. Each step explained
b. Troubleshooting at each step made easy
c. Coming up with final project deliverables
3. Examples of each step in medical science
a. Discovery
b. Data preparation
c. Model Planning
d. Model Building
e. Communicating results
f. Operationalizing and delivery of the final deliverables
Module 4: The Capstone Project
1. Real life application of all the knowledge gained so far
a. Choosing a public health question
b. Developing a hypothesis
c. Going through all the steps of the lifecycle
d. Coming to logical conclusions
e. The key points learned
f. Troubleshooting and getting help
2. Reasons for you to join this course:
a. Getting rid of “fear of numbers” and being independent with data
b. Discussions on problems with each other
c. Active question answer board & Sharing experiences
d. Future collaborations and developing a vibrant Network of DataDoctors
e. Building Efficient Research teams – Getting published
f. Being the sexiest doctors on the planet 😉
Don’t forget to subscribe the youtube channel and click on the notifications icon so that you won’t miss the upcoming episodes.
Also, I will be uploading course materials and exercise files on this website so keep checking for latest updates.
Course Information
Course Instructor
Dr sb
It’s been weeks I was looking for exactly what you are offering.
I want to make my career in Data science, please advise where to start from. I am specialist physician with postgraduate diploma in medical informatics.
Regards
Dear azkar, I am sorry for not being to post any new material as I have been busy lately. I will get back to it soon. Regarding where to get started, you can always plan on doing a master’s in data science or a certification from a reputable institution like UC Berkeley or Cornel. If you just want a jump start then a vendor certification from Dell is not bad as well. But it’s more about self learning and practice than getting degrees.
I hope that satisfies your question. Thanks
Dear Shoaib
Thanks for the reply. I however have sent an email to you as well just today for some personalized advice and shall follow your guidance there.
Kind regards,
Azkar
Sure dear azkar. Why not.