Data Science Course - Part 2: Intermediate/Advanced Scientific Computing for Planners, Engineers, and Scientists

2018 Data Science 2  - Banner.png
Event Date: 
Wednesday, August 8, 2018, 9:00am PDT to Friday, August 10, 2018, 5:00pm PDT
Portland State University, Urban Center, 506 S.W. Mill St., Room 303
Liming Wang, Ph.D., Portland State University
$500 (Discount applies if you attend Part 1 and 2)
PDH: 21 | AICP: 21

This summer we're hosting a two-part data science course. You can register for one or the other– or attend both parts at a discount: Data Science Course 2018, Part 1: Introduction to Scientific Computing for Planners, Engineers, and Scientists



Did you ever feel you are “drinking from a hose” with the amount of data you are attempting to analyze? Have you been frustrated with the tedious steps in your data processing and analysis process and thinking, “There’s gotta be a better way to do things”? Are you curious what the buzz of data science is about? If any of your answers are yes, then this course is for you.

Classes will all be hands-on sessions with lecture, discussions and labs. Participants can choose to sign up for one or both courses. For more information, download the syllabus (PDF).

Agenda: Part Two - Intermediate/Advanced Course
  1. The import-tidy-transform-visualize-model-communicate workflow
  2. The tidyverse suite of packages (dplyr, tidyr, ggplot2, and purrr)
  3. R Markdown
  • August 6-7 Part One: Introduction to Scientific Computing - $350
  • August 8-10 Part Two: Intermediate/Advanced Scientific Computing - $500 
  • DISCOUNT: If you attend both Part One and Part Two - $750
Prerequisites for Intermediate/Advanced Course

To sign up for only the advanced portion of the course (and skip the "Introduction to Scientific Computing) students need to:

  • Know the difference between a vector, matrix, and data frame and how to convert between each other;
  • How to use and create R functions;
  • Know what apply() does.

    Liming Wang, Ph.D., Portland State University

    Liming Wang is an assistant professor in PSU's Toulan School of Urban Studies & Planning. He teaches courses in Travel Demand Modeling, Transportation and Land Use, and Data Analysis Methods. His research takes a data-driven approach to address challenging issues in planning, in particular those intersecting land use and transportation. His recent research projects include data integration techniques for transportation and land use modeling, development and evaluation of comprehensive performance measures for transportation and land use systems, and regional strategic planning tools.

    Professional Development

    This course is eligible for 21 hours of professional development credit for AICP (see our provider summary). We can provide an electronic attendance certificate for other types of certification maintenance.

    This course was developed as part of a NITC education project: Introduction to Scientific Computing for Planners, Engineers, and Scientists