sloisate / ds4ph-bme

A github repo for the Data Science in Public Health and Biomedical Engineering Course

Introduction

A github repo for the Data Science in Biomedical Engineering and Data Science for Public Health Courses.

JHU academic calendar JHBSPH academic calendar

Course location / time: Classes will be done asyncronously. Recorded lectures will be posted on the Teams site for the class. In addition, there will be two office hours / live lectures / live coding sessions per week on Tuesdays and Thursdays. These live sessions are not required and will not be recorded. Students are welcome to attend 0, 1 or both. The two within a day will be highly redudant. However, they will be highly essential for most students in the class. In addition, zoom meetings with instructor are available on request. If you have a conflicting class(es), you should be able to take this class provided you can make some of the live lecture times.

Times of live sessions

• 8:30 AM - 9:50 AM
• 1:30 PM - 2:45 PM

TA office hours:

• 9:00 - 10:00 Friday

Course instructor: Brian Caffo

Course instructor and TA communication: Teams

I cannot stress enought the need to be active on Teams for the class. Much of the discussion will occur there. New announcements will be made there.

Video conferencing links

Video conferencing links will be sent via the Teams site and initally emails to avoid zoom bombers.

Grading:

• There will be once weekly online form submissions (quizzes) / projects / assignments due Mondays at 5:00 PM, unless otherwise noted. These will be based on points and your percentage of total points will represent 70% of the grade. The specific format of the evalutation will be communicated each week.
• These can be handed in and amended anytime up until the due date
• There will be one capstone project that represents 30% of the total grade. This can be done in teams.
• Every evaluation is open book, open internet ....
• You may not consult with fellow students on any quiz prortion of the assignment.
• You may consult with fellow students on any coding project or assigment (other than a quiz)
• All work submitted must be your own. Copying or plagiarism will be considered a breach of student conduct.
• If doing a team capstone project, seperate github submissions must be made and the role of each team member delineated in the readme file.

Curriculum

• Motivation
• Data science tools
• R programming
• Basic Python
• Reproducible report writing
• Exploratory data analysis / interactive graphs
• Developing data products
• Probability [NOT COVERED]
• Statistical inference [NOT COVERED]
• Data resampling methods [NOT COVERED]
• Linear Models / regression
• Generalized linear models
• Penalization and extension of regression models and glms
• Neural networks
• Capstone project

Course communication

All course communcation will come be over the Teams site 2021 Advanced Data Science for Public Health and BME Teams site.

Important computing resources

• Rstudio cloud
• Colab notebooks
• Anaconda
• R
• Rstudio
• Shinyapps.io
• github