Fall 2022 Student Learning Hub Courses Announced

• Instructor: Hector Landes, New York University
• Hands-on exercise: Yes
• Level: No prior experience required.
• Schedule: Wednesday October 26, 2022, 1:00pm – 2:00pm
• Description: This course will be a general introduction to how to use open data for transportation projects. It will start with a short lecture to introduce open-data sources and software to use for data engineering with a focus on demographic, traffic, economic, and safety data. The second part will be a tutorial on how to retrieve data from these sources, how to clean them, manipulate them, and finally visualize them. Finally, this course will also cover how to troubleshoot during data pre-processing and how to overcome an error in either the code or the data. Hands-on exercises on how to use Excel, Tableau, Jupyter Notebook, and QGIS to process the data will be presented.

RSVP Link:  https://nyu.zoom.us/meeting/register/tJUkdOGrpzopHdKc3pIr6ooE1l4gFmSvR6_X

• Instructor: Talha Azfar, Ph.D Candidate at UTEP
• Hands-on exercise: Yes
• Level: No prior experience required.
• Schedule: Friday, November 4, 2022, 1:00pm – 2:00pm
• Description: Realistic digital geographical models of real-world locations are a necessary starting point for digital twin applications, especially for simulation and visualization. This presentation will cover efficient and convenient procedures to create a 3D digital model of the UTEP campus along with the road network on the Unreal Engine project for CARLA, a driving simulator. This can enable applications like computer vision, traffic simulation, and autonomous driving experimentation.  It can serve as a testbed for connected sensors and synchronized databases towards a complete digital twin.

RSVP Link: https://nyu.zoom.us/meeting/register/tJwucu-trzsjHNFtuukA1j0a3NOso7CrEHl7

• Instructor: Zhanhang Li, Rutgers University
• Hands-on exercise: Yes
• Level: No prior experience required.
• Schedule: Wednesday, November 9, 2022, 1:00pm – 2:00pm
• Description: This course will provide students with a foundational understanding of machine learning models and degradation processes. With the bridge degradation modeling case study, students will learn about different types of neural networks, their strengths, and context of application. Case studies and live demos will be provided using Artificial Neural Network (ANN) (Multilayer Perceptron [MLP]) and Convolutional neural network (CNN) for bridge rebar degradation modeling.

RSVP Link:  https://nyu.zoom.us/meeting/register/tJEtdeGvrT4sHNX9YTaN1LWeZfwlr8BRRrfH

• Instructor: Hella Alnajjar, New York University
• Hands-on exercise: Yes
• Beginner level: No prior experience required.
• Schedule: Wednesday, November 16, 2022, 1:00pm – 2:00pm
• Description: This course is for students who want to learn how to conduct, distribute, and analyze a survey-based study using Qualtrics, a powerful online survey tool, for research purposes. The lesson will include hands-on exercises on how to create sets of questions of various types, import data, set up a display or skip logic for a question, and how to effectively visualize, export and analyze the data collected.

RSVP Link:  https://nyu.zoom.us/meeting/register/tJIqfuirrzIqHdyrCYLtknQy9CX0XXxGJHYi