Syllabus

Key Points on Syllabus

• Instructor Information and Office Hours
   
• Course Format and Content
   
• Attendance and Participation
   
• Mid-term Exam
   
• Homework
   
• Course Project
  -  Proposal
  -  Final report

Instructor Information and Office Hours

• Hui Hu, PhD
   
• Office: CTRB 4224
   
• Email: huihu@ufl.edu
   
• Phone: 352-294-5944
   
• Office hours: By appointment

Course Format

• 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 Content

• Course Overview
  - VM setup, R crash course
• SQL
  - Basic SQL
  - Data models and relational SQL
  - Many-to-many relationships in SQL
• Access web data
  - Query APIs
• Spatial data
  - PostGIS
• NoSQL databases
  - MongoDB
• Big Data
  - Spark

Homework

• 6 homework assignments
  -  5% each
  -  the highest 5 grades will count towards the final grade
   
• Often simple programming exercises
   
• Requirements:
  -  turn in assignment no later than the due time
  -  late assignment will NOT be accepted
  -  no handwritten assignment
  -  DO NOT copy others' work

Mid-term Exam

• 35%
   
• Take-home, 1 week to complete
   
• Focus on SQL

Course Project

Option A

Option B

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

Midterm

• 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

o Timeline

Final

• 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.

Grading

• 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