Industry Workshop

There are no immediate plans to offer the Data Science Industry Workshop again, but all of the material presented in the workshop, including the lectures, code, and practice exercises are posted on the Harvard Dataverse here and are freely available.

MoWaTER PRO: Data Science Short Course 2022

Visualization, Analysis, and Modeling in R for the Water Professional

Learn basic data science skills essential to water professionals taught by environmental statisticians and engineers.

To download R and RStudio, see this written explanation.

This is a 5-day virtual workshop that meets once a week on following days:

September 7, 2022 (Wednesday)
September 14, 2022 (Wednesday)
September 21, 2022 (Wednesday)
September 28, 2022 (Wednesday)
October 5, 2022 (Wednesday)

Each daily session will be live from 2 pm to 5 pm Eastern Time, and the following topics will be covered each day:

Pre-Workshop Preparation: Download R and RStudio and R and learn basic navigation.
Day 1 Data Wrangling: Apply data cleaning and blending techniques to create cohesive datasets.
Day 2 Data Visualization: Visualize and explore real industry data.
Day 3 Statistical Modeling: Learn the basics of statistical modeling and interpretation.
Day 4 Machine Learning: Explore machine learning models.
Day 5 Problem Walkthrough: Illustration of a complete problem workflow.

Data Science Short Course Flyer

Key Points

Course instructors are
- Dr. Amanda Hering, Professor of Statistical Science at Baylor University
- Dr. Kathryn Newhart, Assistant Professor of Environmental Engineering at US Military Academy
Course is also developed in conjunction with
- Dr. Tzahi Cath, Professor of Environmental Engineering at Colorado School of Mines
- Dr. Doug Nychka, Professor of Statistics at Colorado School of Mines
Cost is $1,000 per participant, and registration is capped at 25 participants.
Live sessions will be recorded and available for 180 days afterward.
Course materials include all code, example datasets, and notes.
Questions? Contact Dr. Amanda Hering at mandy_hering@baylor.edu.

Reviews From Prior Participants

Very clear and relatable to the water/wastewater industry.
I feel like I have some great tools and best practices that I can use to analyze our facility's data. The workshop was a great introduction to R and machine learning/statistical modeling in general since I had not previously had experience with the concepts of random forests, lasso, tensor flow, etc.
I sometimes suffer from analysis paralysis, and this workshop challenged my perception of statistics and machine learning: I used to think that it is inaccessible for me but the workshop made me realize that using these methods is feasible with enough time and dedication! Thank you.

Commonly Asked Questions

What is the purpose of this short course?

This short course provides a hands-on learning environment and practice of modern data science methods tailored to water professionals. Other options for learning data science do exist, but no others have been designed with only working water/wastewater (W/WWT) professionals in mind. Examples will use real data from W/WWT utilities and consultants, and methods and issues specific to W/WWT data will be covered.
How much does it cost, and what is included in the cost?

The fee to participate in this short course is $1,000 per participant. This fee includes access to the following:
- One asynchronous 'pre' course session and five synchronous virtual sessions
- Recordings of all sessions (available up to 90 days after the workshop)
- eBook of course content along with demonstration datasets and code
- Virtual office hours for personalized attention
When is it?

This is a 5-day short course is spread over 5 weeks to provide more flexibility for participants. Sessions will be held synchronously online via Zoom on September 7th, 14th, 21st, 28th, and October 5th from 2-5pm EDT. If you are unable to attend a session, you will be able to view the recording and attend office hours for additional assistance.
What do I get out of it?

Each participant will receive a certificate of completion at the end of the short course for 15 contact hours. Participation can count towards continuing education/professional development hours for the following states' PE boards that do not approve providers individually: Alabama, Alaska, Arkansas, Delaware, Georgia, Idaho, Illinois, Iowa, Kansas, Kentucky, Maine, Michigan, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Hampshire, New Mexico, North Dakota, Ohio, Oklahoma, Oregon, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, West Virginia, Wisconsin, and Wyoming.
Who should attend this short course?

This short course is intended for water and wastewater consultants, engineers, or professionals who encounter complex datasets (e.g., process and lab data) and want to expedite and improve their analysis workflow.
What are the prerequisites?

No prior knowledge is expected or required. However, it is expected that each participant will be able to install R (a programming language), RStudio (a software that facilitates writing R code), and the R packages necessary to interact with the material. An up-to-date computer and good WiFi connections are needed to participate.
What material will be covered?

Prior to the short course, there will be material to introduce participants to the R language and programming in the RStudio environment. Then, each day of the short course will focus on a different topic. The five sessions will cover introductory data wrangling, data visualization, statistical modeling, machine learning, and a full-scale utility analysis demonstration.
Why was this short course developed?

As part of a National Science Foundation funded program, we have recognized a need for data science training in the W/WWT community that is specific to their problems, and this short course is designed to address that need. In addition, this course raises money to support undergraduate students to do research on W/WWT problems in the summer.