Registration for this class is by application. Please see the details and application links below.
This 10-week class covers the basics of programming in Python for data science projects in health sciences. It includes a general look at data science and algorithmic concepts as well as specific topics in coding, namely the understanding and tools needed to clean data, create data visualizations, and share reproducible results. Learners will be asked to perform these tasks for a final project, which focuses on a provided dataset relating to health research. The class experience is largely asynchronous, though learners will be expected to meet online a few times during the course to discuss class materials and their final project ideas.
Each weekly module will contain readings (e.g., articles, book chapters, videos, website content), a discussion board for learners to answer questions about the materials, and an assignment. Learners will also meet a handful of times with community experts, experienced data science librarians, to discuss the field and class assignments.
- Pre-Work Module: Introduction & Course Setup
- Module 1: Introduction to Data Science & Algorithmic Concepts
- Module 2: Introduction to Python
- Module 3: Python Advanced Concepts, Part 1
- Module 4: Python Advanced Concepts, Part 2
- Module 5: Data Cleaning Python
- Module 6: Data Visualization in Python
- Break: Catch-Up Week
- Module 7: Creating and Sharing Reproducible Data Science Projects
- Module 8: Final Project
- Module 9: Final Presentations
Participation for this course is capped at 75 learners, so if you are interested in applying to register for this course, please commit to spending 4 total hours per week engaging with the course readings and assignments for the full 10 weeks of the course. Also, learners will be required to have access to Google Drive and Google Colaboratory to participate in this course.
There will also be 10 community experts in the course to help learners. Please see below for more information on applying to be a community expert.
To be considered for enrollment as a learner in this course, please submit the following form by Sunday, December 1, 2024 at 11:59 p.m. Eastern Time:
https://www.nnlm.gov/form/ncds-fundamentals-of-health-lear
To be considered as a community expert to help learners in this course, please submit the following form by Sunday, December 1, 2024 at 11:59 p.m. Eastern Time:
Upon completion of the Fundamentals of Health Data Science, learners will be able to do the following:
- Employ analytical thinking to solve data science problems with step-by-step procedures.
- Prepare data using ethical practices to maintain research integrity and avoid bias.
- Use Python programming techniques to clean and analyze datasets.
- Communicate results to stakeholders using best practices for visualizing and reporting data.
- Explain the importance of reproducibility in working with data and sharing research results.