PHC7065 CRITICAL SKILLS IN DATA MANIPULATION FOR POPULATION SCIENCE
Hui Hu Ph.D.
Department of Epidemiology
College of Public Health and Health Professions & College of Medicine
January 11, 2021
Virtual machine setup
Linux terminal and Git
Key Points on Syllabus
- Instructor Information and Office Hours
- Course Format and Content
- Attendance and Participation
- Mid-term Exam
- Course Project
- Final report
Instructor Information and Office Hours
- All lectures and labs will be recorded and released on the canvas every Monday.
- Live recitation sessions:
- ~ 1 hour each week
- TA will answer your questions and explain solutions to your homework and exam
- Participation is mandatory (except for students in the CPE program)
- Course Overview
- VM setup, R crash course
- Basic SQL
- Data models and relational SQL
- Many-to-many relationships in SQL
- Access web data
- Query APIs
- Spatial data
- NoSQL databases
- Big Data
- 6 homework assignments
- 5% each
- the highest 5 grades will count towards the final grade
- Often simple programming exercises
- turn in assignment no later than the due time
- late assignment will NOT be accepted
- no handwritten assignment
- DO NOT copy others' work
- Take-home, 1 week to complete
- Focus on SQL
Pick one article from a list of publications (will be made available mid-February), and write codes to reproduce its data engineering and descriptive analyses
Come up your own ideas for the course project. It is required to include at least ONE non-traditional data source (e.g. spatial data, web data, etc.) other than the traditional survey data
Course Project (continued)
- You can work individually or work as a team
- If choose to work as a team:
- each team can have up to 2 members
- clearly delineate roles and responsibilities of each team member
- Project Due:
- Feb 22, 2021: form a project team
- March 8, 2021: project proposal
- Apr 12, 2021: final presentation
- Apr 19, 2021: final project report
- Project proposal:
- Cover Page: Include title and list of team members.
- Project description: Up to one (1) page.
- Literature cited (no page limit); please follow the Vancouver style.
- Proposals must use single column and single spacing; Arial or Times New Roman font; font size no smaller than 11 point; tables and figure labels can be in 10 point; 0.5 inch margins.
o Specific Aims/Objectives: for those choosing option A, please cite the article you’d like to reproduce and briefly summarize the specific aims/objectives of the article. For those choosing option B, please state your aims/objectives.
o Data Source: please provide details about the data and how it can be accessed
o Preliminary Data Pipelines: please briefly describe the data engineering steps involved in this project
- For those choosing option A, the project report should be structured as an R Markdown Notebook, with all the codes and explanations to the codes.
- For those choosing option B, please structure the report to include:
- Title (14 point typeface) and names of each team member
- Abstract: no more than 250 words summarizing the project.
- Introduction: a short background and objective(s) of the study.
- Methods: design, setting, dataset, approaches, and main outcome measurements.
- Results: key findings
- Discussion: key conclusions with direct reference to the implications of the methods and/or results.
- References: please follow the Vancouver style.
- Attendance and participation: 5%
- Homework: 25%
- Mid-term exam: 35%
- Project proposal: 5%
- Final project presentation: 10%
- Final project report: 20%
Virtual Machine Setup
Linux Terminal and Git
By Hui Hu